Communication apparatus and communication method

ABSTRACT

A communication apparatus calculates a residual component by noting one of a given plurality of transmitted signals and by canceling a component corresponding to a candidate/candidates for the other/others of the plurality of transmitted signals from a signal corresponding to one of a plurality of received signals. The communication apparatus determines a candidate for the given transmitted signal by selecting a value closest to the residual component from among the values that the given transmitted signal can take, and obtains a plurality of candidate groups by changing that given transmitted signal, each candidate group being constructed as a collection of candidate sets each comprising a candidate for that given transmitted signal and a candidate/candidates for that other transmitted signal/signals. Then, the communication apparatus selects transmitted signal candidate sets that are common to the plurality of candidate groups and estimates the plurality of transmitted signals using the selected candidate sets.

CROSS-REFERENCE TO RELATED APPLICATION

This application is based upon and claims the benefit of priority of theprior Japanese Patent Application No. 2010-106243, filed on May 6, 2010,the entire contents of which are incorporated herein by reference.

FIELD

The embodiments discussed herein are related to a communicationapparatus and communication method wherein signals transmitted from aplurality of different antennas are received using a plurality ofantennas.

BACKGROUND

There has long been a need to enhance data transmission speed inwireless communications. To address this, work on next-generation datacommunication standards, such as Long Term Evolution (LTE) has beenproceeding. In high-speed data communication standards such as LTE,Multiple Input Multiple Output (MIMO) technology has been attractingattention, since it can apparently increase the bandwidth bytransmitting and receiving signals in parallel using multiple antennasat both the transmitting and receiving ends.

In a communication system using MIMO technology, a transmittingapparatus equipped with a plurality of antennas splits one or more datastreams into a plurality of signals for transmission. The transmittingapparatus transmits each signal via one of the antennas. On the otherhand, a receiving apparatus, which is also equipped with a plurality ofantennas, receives the transmitted signals from the transmittingapparatus by the respective antennas. The receiving apparatus thendemultiplexes the simultaneously transmitted signals from the signalsreceived by the respective antennas. To demultiplex the transmittedsignals, a known method such as Minimum Mean Square Error (MMSE) orMaximum Likelihood Detection (MLD) is used. A receiving apparatus usingMLD compares the actually received set of signals with each of the setsof received signals estimated from the sets of candidates for the likelytransmitted signals, selects the transmitted signal candidatescorresponding to the mostly likely set among the estimated sets, andtakes the thus selected signal candidates as the actually transmittedsignals. To compare the actually received set of signals with each ofthe sets of received signals estimated from the sets of transmittedsignal candidate, the receiving apparatus using MLD calculates a metricsuch as the squared Euclidian distance between the two received signalsets.

Compared with a linear demultiplexing method such as MMSE, MLD canachieve excellent reception characteristics. However, the amount ofcomputation that MLD performs in order to demultiplex the transmittedsignals from the received signals is larger than the amount ofcomputation that a linear demultiplexing method such as MMSE performs inorder to demultiplex the transmitted signals. In particular, in the caseof MLD, the number of metric calculations increases exponentially as thenumber of simultaneously transmitted signals and the number of valuesthat the modulation scheme used for transmission can take increase.

In view of the above, MLD techniques that can reduce the amount ofcomputation have been proposed (for example, refer to: JapaneseLaid-Open Patent Publication Nos. 2006-121348 and 2009-33636; K. J. Kimand J. Yue, “Joint channel estimation and data detection algorithms forMIMO-OFDM systems,” in Proc. Thirty-Sixth Asilomar Conference onSignals, Systems and Computers, Nov. 2002, pp. 1857-1861; K. Higuchi, H.Kawai, N. Maeda, and M. Sawahashi, “Adaptive Selection of SurvivingSymbol Replica Candidates Based on Maximum Reliability in QRM-MLD forOFCDM MIMO Multiplexing,” Proc. of IEEE Globecom 2004, November 2004,pp. 2480-2486; and M. Siti and M. P. Fitz, “Layered Orthogonal LatticeDetector for Two Transmit Antenna Communications,” in Proc. AllertonConference on Communication Control and Computing, Sept. 2005).

For example, K. J. Kim and J. Yue describe using QRM-MLD which reducesthe number of metric calculations by combining QR decomposition with Malgorithm. Suppose that the relationship between N transmitted signals(x₀, x₁, . . . , x_(N-1)) simultaneously transmitted from a transmittingapparatus and N received signals (y₀, y₁, . . . , y_(N-1)) received by areceiving apparatus is expressed by the following equation. Here, N isan integer not smaller than 2. Further, the number of transmittedsignals need not be the same as the number of received signals, i.e.,the number of antennas of the receiving apparatus. As long as the numberof antennas of the receiving apparatus is greater than the number ofsimultaneously transmitted signals, the signals can be transmitted andreceived using MIMO technology.

$\begin{matrix}{Y = {{{HX}\begin{pmatrix}y_{0} \\y_{1} \\\vdots \\y_{N - 1}\end{pmatrix}} = {\begin{pmatrix}h_{0,0} & h_{0,1} & \ldots & h_{0,{N - 1}} \\h_{1,0} & h_{1,1} & \ldots & h_{1,{N - 1}} \\\vdots & \vdots & \ddots & \vdots \\h_{{N - 1},0} & h_{{N - 1},1} & \ldots & h_{{N - 1},{N - 1}}\end{pmatrix}\begin{pmatrix}x_{0} \\x_{1} \\\vdots \\x_{N - 1}\end{pmatrix}}}} & (1)\end{matrix}$

where the matrix H represents the effective channel matrix describingthe correspondence between the transmitted signals and the receivedsignals. In equation (1), noise added to the transmitted signals isomitted for simplicity. In QRM-MLD, the effective channel matrix H isdecomposed into a unitary matrix Q and a triangular matrix R, andexpressed as shown in the following equation.

$\begin{matrix}{\mspace{79mu} {H = {{{QR}\begin{pmatrix}h_{0,0} & h_{0,1} & \ldots & h_{0,{N - 1}} \\h_{1,0} & h_{1,1} & \ldots & h_{1,{N - 1}} \\\vdots & \vdots & \ddots & \vdots \\h_{{N - 1},0} & h_{{N - 1},1} & \ldots & h_{{N - 1},{N - 1}}\end{pmatrix}} = {\begin{pmatrix}q_{0,0} & q_{0,1} & \ldots & q_{0,{N - 1}} \\q_{1,0} & q_{1,1} & \ldots & q_{1,{N - 1}} \\\vdots & \vdots & \ddots & \vdots \\q_{{N - 1},0} & q_{{N - 1},1} & \ldots & q_{{N - 1},{N - 1}}\end{pmatrix}\begin{pmatrix}r_{0,0} & r_{0,1} & \ldots & r_{0,{N - 1}} \\0 & r_{1,1} & \ldots & r_{1,{N - 1}} \\\vdots & \ddots & \ddots & \vdots \\0 & \ldots & 0 & r_{{N - 1},{N - 1}}\end{pmatrix}}}}} & (2)\end{matrix}$

By multiplying both sides of equation (1) from the left by the Hermitianconjugate Q^(H) of the unitary matrix Q, the following equation isobtained.

$\begin{matrix}{Z = {{Q^{H}Y} = {{Q^{H}{QRX}} = {{{RX}\begin{pmatrix}z_{0} \\z_{1} \\\vdots \\z_{{N - 1}\;}\end{pmatrix}} = {\begin{pmatrix}r_{0,0} & r_{0,1} & \ldots & r_{0,{N - 1}} \\0 & r_{1,1} & \ldots & r_{1,{N - 1}} \\\vdots & \ddots & \ddots & \vdots \\0 & \ldots & 0 & r_{{N - 1},{N - 1}}\end{pmatrix}\begin{pmatrix}x_{0} \\x_{1} \\\vdots \\x_{{N - 1}\;}\end{pmatrix}}}}}} & (3)\end{matrix}$

where the vector z=(z₀, z₁, . . . , z_(N-1)) is the unitary transformedvector of the received signal vector which is obtained by the product ofthe received signal vector Y and the matrix Q^(H). As shown in equation(3), the number of transmitted signals associated with each element ofthe unitary transformed vector z differs from one element to another.For example, only the transmitted signal x_(N-1) is associated with thesignal On the other hand, N transmitted signal x₀ to x_(N-1) areassociated with the signal z₀.

The receiving apparatus calculates as the metric the squared Euclidiandistance between each of the values of z₀ to z_(N-1) obtained from theactually received signals and each of the values of z₀ to obtained bysubstituting the set of symbol replicas corresponding to the likelytransmitted signals into the vector X in equation (3). The symbolreplicas are signals tentatively set by the receiving apparatus. In MLD,the receiving apparatus estimates that the set of symbol replicas thatminimizes the sum of the metrics obtained for all of z₀ to z_(N-1)represents the actually transmitted signals.

The receiving apparatus using QRM-MLD calculates the metrics for thesignals z₀ to z_(N-1) in order of increasing number of transmittedsignals associated therewith. For example, in equation (3), the numberof transmitted signals associated with the signal z_(N-1) is thesmallest. Accordingly, the receiving apparatus calculates in the firststage the metrics for the signal z_(N-1), and then calculates in thesecond stage the metrics for the signal z_(N-2) which is the secondsmallest in terms of the number of transmitted signals associatedtherewith. In the m-th stage, the receiving apparatus calculates themetrics only for M symbol replicas selected in increasing order of themetrics calculated for the signal z_(m-1) in the immediately precedingstage. For example, suppose that M=3 and that the transmitted signals x₀to x_(N-1) are modulated by 64-QAM. In this case, there are 64 symbolreplicas for each transmitted signal. Then, since only the transmittedsignal x_(N-1) is associated with the signal z_(N-1), the receivingapparatus first calculates the metrics for the 64 symbol replicasc_(N-1,0) to c_(N-1,63) corresponding to the transmitted signal x_(N-1).Suppose that the symbol replicas corresponding to the three metricsselected in increasing order of the metrics are C_(N-1,a), C_(N-1,b),and C_(N-1,c) (where 0≦a, b, c≦63 and a≠b≠c). In this case, thereceiving apparatus selects only the three symbol replicas C_(N-1,a),C_(N-1,b), and c_(N-1,c) for the transmitted signal x_(N-1) whencalculating the metrics for the signal z_(N-2). Then, the receivingapparatus calculates the metric for each symbol replica set made up ofone of the three symbol replicas C_(N-1,a), C_(N-1,b), and C_(N-1,c) andone of the 64 symbol replicas c_(N-2,0) to C_(N-2,63) that thetransmitted signal x_(N-2) can take. Since there is no need to calculatethe metrics for all the symbol replica sets, the receiving apparatususing QRM-MLD can reduce the amount of computation.

Japanese Laid-Open Patent Publication No. 2006-121348 discloses atechnique in which a decision on symbol candidates for a plurality oftransmitted signals is made by separately applying the QRM-MLD method toreceived signals arranged in two different orders and, based on theresult of the decision, outputs a plurality of symbol candidates andtheir likelihood.

K. Higuchi, H. Kawai, N. Maeda, and M. Sawahashi teach an AdaptiveSelection of Surviving Symbol replica candidates based on maximumreliability (ASESS) method that can further reduce the number of metriccalculations compared with QRM-MLD. In the ASESS method, the receivingapparatus obtains residual received signals at each metric calculationstage by subtracting the signal components of the surviving symbolreplica candidates from the received signals obtained by QR-decomposingthe channel matrix and thus orthogonalizing the transmitted signals.Then, based on the residual received signals, the symbol replicacandidates for which the branch metrics are to be calculated are rankedby the receiving apparatus in increasing order of the expected branchmetrics. The receiving apparatus then calculates the branch metrics insequence starting from the highest ranking symbol replica candidate, andallows only the symbol replica candidates whose branch metrics aresmaller than a predetermined threshold value to survive. The ranking ofthe symbol replica candidates is determined by detecting the quadrant towhich the residual received signals belong.

On the other hand, in the Layered Orthogonal Lattice Detector (LORD)method proposed by M. Siti and M. P. Fitz and in the method disclosed inJapanese Laid-Open Patent Publication No. 2009-33636, the receivingapparatus applies QR decomposition to a first channel matrix. Then,based on the upper triangular matrix and unitary matrix obtained by theQR decomposition, the receiving apparatus calculates the metric whensome of the plurality of transmitted signals are of a prescribed value.Further, the receiving apparatus generates a second channel matrix byinterchanging the order of the channels in the first channel matrix.Then, based on the upper triangular matrix and signal vector Z′ obtainedby the QR decomposition of the second channel matrix, the receivingapparatus calculates the metric when some other ones of the plurality oftransmitted signals are of a prescribed value. The receiving apparatusthen estimates the transmitted signals by determining a set of symbolreplicas based on the metric obtained for the first channel matrix andthe metric obtained for the second channel matrix.

SUMMARY

However, in any of the above prior art methods, a large amount ofcomputation has to be performed to estimate the transmitted signals,because each method involves gradually reducing the number oftransmitted signal candidate sets while calculating the metrics for aplurality of transmitted signal candidate sets. As a result, if thesecomputations are to be performed without reducing the communicationspeed, the amount of computing circuitry has to be increased. If theamount of computing circuitry increases, it becomes difficult to reducethe size of mobile apparatus such as a mobile phone if the MIMOtechnology is to be applied to such mobile apparatus. Furthermore, sincethe power consumed by the computing circuitry increases with increasingamount of computation, it is preferable to reduce the amount ofcomputation for battery-driven receiving apparatus such as mobileterminals.

According to one embodiment, there is provided a communicationapparatus. The communication apparatus includes: a plurality ofantennas; a plurality of receiving units which are each coupled to oneof the plurality of antennas, and which respectively acquire receivedsignals by receiving, via the coupled antennas, a plurality of signalstransmitted from a transmitting apparatus having a plurality ofantennas; a candidate group setting unit which, based on a first channelmatrix describing a communication channel between the plurality oftransmitted signals and the plurality of received signals, calculates afirst residual component by canceling a component corresponding to acandidate or candidates for a first other transmitted signal or signalsother than a first transmitted signal among the plurality of transmittedsignals from a first signal corresponding to at least one of theplurality of received signals and having components corresponding to allof the plurality of transmitted signals, determines a candidate for thefirst transmitted signal by selecting a value closest to the firstresidual component from among values that the first transmitted signalcan take, and constructs a first candidate group as a collection ofcandidate sets each comprising a candidate for the first transmittedsignal and a candidate or candidates for the first other transmittedsignal or signals, and which, based on a second channel matrixdescribing a communication channel between the plurality of transmittedsignals and the plurality of received signals, calculates a secondresidual component by canceling a component corresponding to a candidateor candidates for a second other transmitted signal or signals otherthan a second transmitted signal among the plurality of transmittedsignals from a second signal corresponding to at least one of theplurality of received signals and having components corresponding to allof the plurality of transmitted signals, determines a candidate for thesecond transmitted signal by selecting a value closest to the secondresidual component from among values that the second transmitted signalcan take, and constructs a second candidate group as a collection ofcandidate sets each comprising a candidate for the second transmittedsignal and a candidate or candidates for the second other transmittedsignal or signals; a common group searching unit which constructs acommon group by selecting any transmitted signal candidate set that iscommon between the first candidate group and the second candidate group;a metric calculating unit which, for each transmitted signal candidateset contained in the common group, computes an estimated received signalset corresponding to the transmitted signal candidate set, andcalculates a distance between the estimated received signal set and theplurality of received signals; and a signal estimating unit whichestimates that the transmitted signal candidate set that minimizes thedistance represents the set of the plurality of transmitted signals.

The object and advantages of the invention will be realized and attainedby means of the elements and combinations particularly pointed out inthe claims.

It is to be understood that both the foregoing general description andthe following detailed description are exemplary and explanatory and arenot restrictive of the invention, as claimed.

BRIEF DESCRIPTION OF DRAWINGS

FIG. 1 is a diagram schematically illustrating the configuration of acommunication system which includes a receiving apparatus according to afirst embodiment.

FIG. 2 is a diagram schematically illustrating the configuration of astream demultiplexer incorporated in the receiving apparatus accordingto the first embodiment.

FIGS. 3A to 3C are diagrams each depicting the relationship between anestimate of a transmitted signal x₀ and the quadrant to which theestimate belongs.

FIG. 4 is a conceptual diagram illustrating two candidate groups and thetransmitted signal candidate sets common to the two groups.

FIG. 5 is a diagram depicting inverted bit symbols when, for eachinverted bit, a symbol that is closest to the most likely bit isselected as the inverted bit symbol.

FIG. 6 is a diagram depicting inverted bit symbols when, for eachinverted bit, symbols that are closest and second closest to the mostlikely bit are selected as the inverted bit symbols.

FIGS. 7A and 7B are an operation flowchart illustrating a transmittedsignal demultiplexing process.

FIG. 8 is an operation flowchart illustrating the transmitted signaldemultiplexing process.

FIG. 9 is a diagram schematically illustrating the configuration of astream demultiplexer in a receiving apparatus according to a secondembodiment.

FIGS. 10A and 10B are diagrams depicting an example of the positionalrelationship between an estimate v₁ of a transmitted signal x₁ andsymbol replicas.

FIGS. 11A and 11B are an operation flowchart illustrating a transmittedsignal demultiplexing process according to the second embodiment, whichis performed instead of the transmitted signal demultiplexing process ofsteps S101 to S110 illustrated in FIGS. 7A and 7B.

FIG. 12 is a diagram schematically illustrating the configuration of astream demultiplexer in a receiving apparatus according to a thirdembodiment.

FIG. 13 is a diagram depicting one example of a candidate group.

FIG. 14 is a diagram schematically illustrating the configuration of astream demultiplexer in a receiving apparatus according to a fourthembodiment.

FIG. 15 is a diagram schematically illustrating the configuration of abase station apparatus in which the receiving apparatus according to anyone of the embodiments is incorporated.

FIG. 16 is a diagram schematically illustrating the configuration of amobile station apparatus in which the receiving apparatus according toany one of the embodiments is incorporated.

DESCRIPTION OF THE EMBODIMENTS

A receiving apparatus according to one embodiment will be describedbelow with reference to the drawings. Using MIMO technology, thereceiving apparatus receives, via a plurality of antennas, a pluralityof signals transmitted from a transmitting apparatus having a pluralityof antennas. The receiving apparatus then demultiplexes the transmittedsignals from the signals received by the respective antennas. Todemultiplex the transmitted signals, the receiving apparatus obtains twochannel matrices by interchanging the order of the channels betweenthem. Then, the receiving apparatus obtains sets of transmitted signalcandidates for each channel matrix. The receiving apparatus determinesone of the plurality of transmitted signal candidates as being a symbolreplica closest to the residual component calculated by canceling thecomponent corresponding to the other transmitted signal candidate fromthe unitary transformed signal of the received signal having componentsrelating to all of the transmitted signals. The receiving apparatuscalculates the metrics only for the candidate sets common to the twogroups of transmitted signal candidate sets obtained for the two channelmatrices, thus reducing the number of metric calculations each of whichinvolves a large amount of computation.

FIG. 1 is a diagram schematically illustrating the configuration of acommunication system 1 which includes a receiving apparatus 3 accordingto a first embodiment. The communication system 1 includes atransmitting apparatus 2 equipped with two antennas 21-1 and 21-2, aswell as the receiving apparatus 3 which is also equipped with twoantennas 31-1 and 31-2. The transmitting apparatus 2 radiatestransmitted signals as radio signals simultaneously from the respectiveantennas 21-1 and 21-2. On the other hand, the receiving apparatus 3receives the transmitted signals from the transmitting apparatus 2 bythe respective antennas 31-1 and 31-2. The signals received by therespective antennas 31-1 and 31-2 will hereinafter be referred to as thereceived signals. The receiving apparatus 3 recovers the transmittedsignals based on each received signal.

In the present embodiment, the number of antennas mounted on thetransmitting apparatus 2 is only illustrative, and may be set to anynumber not smaller than 2 but not larger than the number that can bephysically mounted on the transmitting apparatus 2. Similarly, thenumber of antennas mounted on the receiving apparatus 3 is onlyillustrative, and may be set to any number not smaller than 2 but notlarger than the number that can be physically mounted on the receivingapparatus 3. Further, the number of antennas mounted on the transmittingapparatus 2 may be made different from the number of antennas mounted onthe receiving apparatus 3.

The transmitting apparatus 2 includes, in addition to the two antennas21-1 and 21-2, a codeword generating unit 22, an encoding unit 23, amodulation unit 24, two transmitting units 25-1 and 25-2, and a controlunit 26. The codeword generating unit 22, the encoding unit 23, themodulation unit 24, the transmitting units 25-1 and 25-2, and thecontrol unit 26 may be provided as separate circuits or may beimplemented together on a single integrated circuit for mounting in thetransmitting apparatus 2.

The codeword generating unit 22 splits transmit data into codewords eachhaving a length defined by the transport block size (TBS) determined bythe control unit 26. The codeword is, for example, MAC-PDU data thatconforms to the media access control (MAC) layer and the protocol dataunit (PDU) layer. The codeword generating unit 22 assigns the generatedcodewords to the encoding unit 23 by referring to the number of streamsdetermined by the control unit 26 for each of the codewords to beencoded by the encoding unit 23. The number of streams represents thenumber of data to be transmitted simultaneously for one codeword. Thecodeword generating unit 22 passes the generated codewords to theencoding unit 23.

The encoding unit 23 applies error correction coding, such asconvolutional coding or Turbo coding, to the codewords received from thecodeword generating unit 22. Further, the encoding unit 23 generatesdata streams by splitting each encoded codeword in accordance with thenumber of streams determined by the control unit 26. Then, the encodingunit 23 supplies the encoded codewords on a stream-by-stream basis tothe modulation unit 24.

The modulation unit 24 quadrature-modulates the data streams receivedfrom the encoding unit 23 in accordance with the modulation mode MODdetermined by the control unit 26. The modulation unit 24 supplies eachdata stream to one of the transmitting units 25-1 and 25-2 in accordancewith the precoding matrix determined by the control unit 26.

The transmitting units 25-1 and 25-2 each generate a transmit signal bysuperimposing the data stream supplied from the modulation unit 24 ontoa carrier wave having a radio frequency. Each of the transmitting units25-1 and 25-2 has a high-power amplifier. Each of the transmitting units25-1 and 25-2 thus amplifies the strength of the transmit signal to adesired level. The transmitting units 25-1 and 25-2 are coupled to theantennas 21-1 and 21-2, respectively, and transmit out the signals viathe respective antennas.

The control unit 26 controls the entire operation of the transmittingapparatus 2. The control unit 26 determines the codeword length, themodulation mode, the number of streams for each codeword, and theprecoding matrix, for example, by referring to the feedback informationreceived from the receiving apparatus 3. Then, the control unit 26 sendsinformation such as the codeword length, the modulation mode, etc. tothe corresponding units in the transmitting apparatus 2. The feedbackinformation includes, for example, a CQI value which indicates thequality of the signal received by the receiving apparatus 3. The controlunit 26 here can demodulate and decode the signal received from thereceiving apparatus 3 via a receiving unit (not shown) coupled to one ofthe antennas and can extract the feedback information from the decodedsignal.

Next, the receiving apparatus 3 according to the first embodiment willbe described. The receiving apparatus 3 includes, in addition to the twoantennas 31-1 and 31-2, two receiving units 32-1 and 32-2, ademodulation unit 33, a decoding unit 36, and a data combining unit 37.The receiving units 32-1 and 32-2, the demodulation unit 33, thedecoding unit 36, and the data combining unit 37 may be provided asseparate circuits or may be implemented together on a single integratedcircuit for mounting in the receiving apparatus 3.

The receiving units 32-1 and 32-2 are coupled to the antennas 31-1 and31-2, respectively. The receiving units 32-1 and 32-2 receive via therespective antennas 31-1 and 31-2 the transmit signals transmitted fromthe antennas 21-1 and 21-2 of the transmitting apparatus 2. Each of thereceiving units 32-1 and 32-2 has a low-noise amplifier which amplifiesthe received signal. Each of the receiving units 32-1 and 32-2 convertsthe frequency of the received signal into the baseband frequency bysuperimposing a signal having an intermediate frequency on the amplifiedreceived signal, and supplies the thus converted received signal to thedemodulation unit 33.

From the signals received from the receiving units 32-1 and 32-2, thedemodulation unit 33 demultiplexes the signals transmitted out from therespective antennas of the transmitting apparatus 2. For this purpose,the demodulation unit 33 includes a channel estimator 34 and a streamdemultiplexer 35.

The channel estimator 34 obtains a channel matrix defining therelationship between the transmitted signals and the received signals.For example, the channel estimator 34 obtains the channel impulseresponse value of a signal known to the transmitting apparatus 2 and thereceiving apparatus 3, such as a pilot signal contained in the signaltransmitted out from each antenna of the transmitting apparatus 2. Then,the channel estimator 34 sets the channel impulse response value as anelement in the channel matrix. In this case, the relationship betweenthe transmitted signals and the received signals is expressed by thefollowing equation using the channel matrix.

$\begin{matrix}{Y = {{{HX} + {n\begin{pmatrix}y_{0} \\y_{1}\end{pmatrix}}} = {{\begin{pmatrix}h_{00} & h_{01} \\h_{10} & h_{11}\end{pmatrix}\begin{pmatrix}x_{0} \\x_{1}\end{pmatrix}} + \begin{pmatrix}n_{0} \\n_{1}\end{pmatrix}}}} & (4)\end{matrix}$

where x₀ and x₁ represent the signals transmitted out from therespective antennas 21-1 and 21-2. The transmitted signal vector X is avector whose elements are the transmitted signals x₀ and x₁. On theother hand, y₀ and y₁ represent the signals received via the respectiveantennas 31-1 and 31-2. The received signal vector Y is a vector whoseelements are the received signals y₀ and y₁. The matrix H indicates thechannel matrix whose elements h_(ij) are each obtained, for example, asa channel impulse response to a pilot signal, as described above. Thevector n indicates the noise vector whose elements n₀ and n₁ representthe noise components contained in the signals received by the respectiveantennas 31-1 and 31-2. The ordering of the channels is not limited tothe above example. For example, the transmitted signals x₀ and x₁ may bethe signals transmitted out from the antennas 21-2 and 21-1,respectively, and y₀ and y₁ may be the signals received via the antennas31-2 and 31-1, respectively. The channel estimator 34 passes the channelmatrix to the stream demultiplexer 35.

Based on the channel matrix, the stream demultiplexer 35 demultiplexesthe transmitted signals from the received signals. The details of thestream demultiplexer 35 will be described later.

The demodulation unit 33 demodulates the demultiplexed transmittedsignals in accordance with the modulation scheme applied to thetransmitted signals, and passes the demodulated signals to the decodingunit 36. Further, the demodulation unit 33 computes the feedbackinformation such as CQI value, etc., to be fed back to the transmittingapparatus 2, and passes the feedback information to a transmitting unitnot shown. The transmitting unit generates a radio signal byquadrature-modulating the feedback-information carrying signal andsuperimposing it onto a carrier wave having a radio frequency. Thetransmitting unit radiates the feedback-information carrying radiosignal from one of the antennas.

The decoding unit 36 reconstructs each encoded codeword by combining thedata streams received from the demodulation unit 33. Then, the decodingunit 36 applies error correction decoding to each encoded codeword. Thedecoding unit 36 supplies the thus decoded codewords to the datacombining unit 37.

The data combining unit 37 recovers the original data by combining thecodewords received from the decoding unit 36. The data combining unit 37supplies the thus recovered original data to other component elements ofthe receiving apparatus 3.

The details of the stream demultiplexer 35 will be described below. FIG.2 is a diagram schematically illustrating the configuration of thestream demultiplexer 35. The stream demultiplexer 35 includes a channelinterchanging unit 41, a QR-decomposition unit 42, a candidate groupsetting unit 43, a common group searching unit 44, a metric calculatingunit 45, a minimum value searching unit 46, an additional metriccalculating unit 47, and a logarithmic likelihood ratio computing unit48. These units constituting the stream demultiplexer 35 may beimplemented as separate computing circuits. Alternatively, these unitsconstituting the stream demultiplexer 35 may be integrated into a singlecomputing circuit implementing the functions of the respective units.

The channel interchanging unit 41 creates a transformed channel matrixH′ by interchanging the order of the columns in the channel matrix H.The relationship between the transmitted signals and the receivedsignals, using the transformed channel matrix H′, is expressed by thefollowing equation.

$\begin{matrix}{Y = {{{H^{\prime}X^{\prime}} + {n\begin{pmatrix}y_{0} \\y_{1}\end{pmatrix}}} = {{\begin{pmatrix}h_{01} & h_{00} \\h_{11} & h_{10}\end{pmatrix}\begin{pmatrix}x_{1} \\x_{0}\end{pmatrix}} + \begin{pmatrix}n_{0} \\n_{1}\end{pmatrix}}}} & (5)\end{matrix}$

The channel interchanging unit 41 passes the transformed channel matrixH′ to the QR-decomposition unit 42.

The QR-decomposition unit 42 includes a first QR-decomposition unit 421and a second QR-decomposition unit 422. The first QR-decomposition unit421 QR-decomposes the channel matrix H received from the channelestimator 35 into a unitary matrix Q and an upper triangular matrix R.The channel matrix H is expressed as shown in the following equation byusing the unitary matrix Q and the upper triangular matrix R.

$\begin{matrix}{H = {{{QR}\begin{pmatrix}h_{00} & h_{01} \\h_{10} & h_{11}\end{pmatrix}} = {\begin{pmatrix}q_{00} & q_{01} \\q_{10} & q_{11}\end{pmatrix}\begin{pmatrix}r_{00} & r_{01} \\0 & r_{11}\end{pmatrix}}}} & (6)\end{matrix}$

Then, the first QR-decomposition unit 421 multiplies both sides ofequation (4) from the left by the Hermitian conjugate Q^(H) of theunitary matrix. In this way, the first QR-decomposition unit 421 obtainsthe unitary transformed vector z by unitary-transforming the receivedsignal vector Y. The relationship between the unitary transformed vectorz, the upper triangular matrix R, and the transmitted signal vector X isexpressed by the following equation.

$\begin{matrix}{z = {{Q^{H}Y} = {{{Q^{H}{QRX}} + {Q^{H}n}} = {{{RX} + {Q^{H}{n\begin{pmatrix}z_{0} \\z_{1}\end{pmatrix}}}} = {{\begin{pmatrix}r_{00} & r_{01} \\0 & r_{11}\end{pmatrix}\begin{pmatrix}x_{0} \\x_{1}\end{pmatrix}} + {\begin{pmatrix}q_{00}^{*} & q_{10}^{*} \\q_{01}^{*} & q_{11}^{*}\end{pmatrix}\begin{pmatrix}n_{0} \\n_{1}\end{pmatrix}}}}}}} & (7)\end{matrix}$

where unitary transformed signals z₀ and z₁ are the elements of theunitary transformed vector z and each have components relating to thereceived signals y₀ and y₁.

The second QR-decomposition unit 422 QR-decomposes the transformedchannel matrix H′ received from the channel interchanging unit 41 into aunitary matrix Q′ and an upper triangular matrix R′. The channel matrixH′ is expressed as shown in the following equation by using the unitarymatrix Q′ and the upper triangular matrix R′.

$\begin{matrix}{H^{\prime} = {{Q^{\prime}{R^{\prime}\begin{pmatrix}h_{01} & h_{00} \\h_{11} & h_{10}\end{pmatrix}}} = {\begin{pmatrix}q_{00}^{\prime} & q_{01}^{\prime} \\q_{10}^{\prime} & q_{11}^{\prime}\end{pmatrix}\begin{pmatrix}r_{00}^{\prime} & r_{01}^{\prime} \\0 & r_{11}^{\prime}\end{pmatrix}}}} & (8)\end{matrix}$

Then, as in the first QR-decomposition unit 421, the secondQR-decomposition unit 422 multiplies both sides of equation (5) from theleft by the Hermitian conjugate Q′^(H) of the unitary matrix. In thisway, the second QR-decomposition unit 422 obtains the unitarytransformed vector z′ by unitary-transforming the received signal vectorY. The relationship between the unitary transformed vector z′, the uppertriangular matrix R′, and the transmitted signal vector X′ is expressedby the following equation.

$\begin{matrix}{z^{\prime} = {{{Q^{\prime}}^{H}Y} = {{{Q^{\prime \; H}Q^{\prime}R^{\prime}X} + {Q^{\prime \; H}n}} = {{{R^{\prime}X} + {Q^{\prime \; H}{n\begin{pmatrix}z_{0}^{\prime} \\z_{1}^{\prime}\end{pmatrix}}}} = {{\begin{pmatrix}r_{00}^{\prime} & r_{01}^{\prime} \\0 & r_{11}^{\prime}\end{pmatrix}\begin{pmatrix}x_{1} \\x_{0}\end{pmatrix}} + {\begin{pmatrix}q_{00}^{\prime*} & q_{10}^{\prime*} \\q_{01}^{\prime*} & q_{11}^{\prime*}\end{pmatrix}\begin{pmatrix}n_{0} \\n_{1}\end{pmatrix}}}}}}} & (9)\end{matrix}$

where unitary transformed signals z′₀ and z′₁ are the elements of theunitary transformed vector z′ and each have components relating to thereceived signals y₀ and y₁.

The first and second QR-decomposition units 421 and 422 can perform theQR decomposition by using such techniques as a Givens rotation, aHouseholder transformation, or a Gram-Schmidt decomposition. TheQR-decomposition unit 42 passes the unitary transformed vectors z and z′and the upper triangular matrices R and R′ to the candidate groupsetting unit 43.

The candidate group setting unit 43 includes a first candidate groupsetting unit 431 and a second candidate group setting unit 432.

The first candidate group setting unit 431 obtains a candidate set fortransmitted signals by using the unitary transformed vector z and uppertriangular matrix R calculated based on the channel matrix H. Referringto equation (7), it is seen that the unitary transformed signal z₀contains the components of both transmitted signals x₀ and x₁.Therefore, based on the expression relating to the unitary transformedsignal z₀ in equation (7), the first candidate group setting unit 431obtains as an estimate of the transmitted signal x₀ the residualcomponent calculated by canceling the component relating to thecandidate for the transmitted signal x₁ from the unitary transformedsignal z₀. Then, the first candidate group setting unit 431 obtains apair made up of a given candidate c_(1i) for the transmitted signal x₁and the value that is closest, among the values that the transmittedsignal x₀ can take, to the estimate of the transmitted signal x₀ whenthe transmitted signal x₁ is represented by that given candidate, andsets this pair as the transmitted signal candidate set.

When the transmitted signal x₁ is c_(1i) (i=0, 1, . . . , m₁-1), theestimate u_(0i) of the transmitted signal x₀ is expressed by thefollowing equation. Here, c_(1i) is a symbol replica which is generatedby the receiving apparatus 3 as one of the possible signal values thatthe transmitted signal x₁ can take in the modulation scheme applied tothe transmitted signal x₁. Here, c_(1i) is expressed by a combination ofa real (I) signal and an imaginary (Q) signal. On the other hand, m₁represents the number of values that can be taken in the modulationscheme applied to the transmitted signal x₁. For example, if themodulation scheme is 16-QAM, m₁=16, and if the modulation scheme is64-QAM, m₁=64.

$\begin{matrix}{u_{0i} = \frac{z_{0} - {r_{01}c_{1i}}}{r_{00}}} & (10)\end{matrix}$

The first candidate group setting unit 431 detects, for example, thequadrant to which the estimate u_(0i) belongs, in order to determine thecandidate for the transmitted signal x₀ that is closest to the estimateu_(0i).

The quadrant detection will be described with reference to FIGS. 3A to3C. As an example, it is assumed that the modulation scheme applied tothe transmitted signal x₀ is 64-QAM. In FIGS. 3A to 3C, the abscissarepresents the I signal component, and the ordinate represents the Qsignal component. Points 301 are the signal points corresponding to thesignal values that the transmitted signal x₀ can take. For example,point 301 a represents the signal value corresponding to symbol“101111”. Asterisk 310 indicates the estimate u_(0i) obtained bysubstituting the symbol replica c_(1i) into equation (10). In theillustrated example, the I and Q signal components of the estimateu_(0i) are both negative values.

As depicted in FIG. 3A, the estimate u_(0i) is located in the thirdquadrant 320 because the I and Q signal components are both negativevalues. Accordingly, the first candidate group setting unit 431estimates that the transmitted signal x₀ is represented by one of thesignal values belonging to the third quadrant.

Next, the first candidate group setting unit 431 detects the quadrant towhich the estimate u_(0i) belongs in a coordinate plane that has itsorigin O′ at a point represented by a signal value (−4/√42, −4/√42)corresponding to the center of the third quadrant to which the estimateu_(0i) belongs. That is, the first candidate group setting unit 431obtains an estimate u′_(0i) by subtracting from the estimate u_(0i) thesignal value (−4/√42, −4/√42) corresponding to the center of the thirdquadrant, and checks whether the I and Q signal components of theestimate u′_(0i) are positive or negative. In the illustrated example,the estimate u_(0i) is located in the first quadrant 330 of the planecentered at the origin O′, as depicted in FIG. 3B. Accordingly, thefirst candidate group setting unit 431 estimates that the transmittedsignal x₀ is represented by one of the signal values belonging to thefirst quadrant 330 of the plane centered at the origin O′.

The first candidate group setting unit 431 repeats the above quadrantdetection process until the signal value closest to the estimate u_(0i)is found. In the illustrated example, the first candidate group settingunit 431 detects the quadrant to which the estimate u_(0i) belongs in acoordinate plane that has its origin O″ at a point represented by asignal value (−2/√42, −2/√42) corresponding to the center of the firstquadrant 330 to which the estimate u_(0i) belongs in the plane centeredat the origin O′. That is, the first candidate group setting unit 431obtains an estimate u″_(0i) by subtracting from the estimate u_(0i) thesignal value (−2/√42, −2/√42) corresponding to the center of the firstquadrant 330, and checks whether the I and Q signal components of theestimate u″_(0i) are positive or negative. As depicted in FIG. 3C, theestimate u_(0i) is located in the second quadrant 340 of the planecentered at the origin O″. The second quadrant 340 corresponds to onesymbol “110001”. Therefore, the signal value corresponding to the symbol“110001” is the closest to the estimate u_(0i).

Then, when the transmitted signal x₁ is c_(1i), the first candidategroup setting unit 431 sets the signal value corresponding to the symbol“110001” as the candidate for the transmitted signal x₀. Hereinafter,the candidate for the transmitted signal x₀ thus set when thetransmitted signal x₁ is c_(1i) is denoted by x₀ ^((min))(c_(1i)).

In this way, by using the quadrant detection, the first candidate groupsetting unit 431 can reduce the number of calculations, such asmultiplications, that involve a larger amount of computation, and canthus reduce the amount of computation for finding x₀ ^((min)) (c_(1i)).

When calculating the estimate u_(0i) in accordance with equation (10),an operation to divide (z₀−r₀₁c_(1i)) by r₀₀ is performed. In view ofthis, the first candidate group setting unit 431 may calculate theestimate u_(0i) as the numerator term (z₀−r₀₁c_(1i)) on the right-handside of equation (10), and may set the origin in the second and laterquadrant detections by taking a point represented by a value obtained bymultiplying by r₀₀ the signal value corresponding to the center of thequadrant to which the estimate u_(0i) is detected to belong. Since thisserves to reduce the number of division operations, the first candidategroup setting unit 431 can reduce the amount of computation for findingx₀ ^((min))(c_(1i)).

By repeating the above process for each symbol replica c_(1i) (i=0, 1, .. . , m₁-1), the first candidate group setting unit 431 obtains a firstcandidate group 100 ₁ which is a collection of candidate sets for thetransmitted signals x₀ and x₁. The first candidate group φ₁ is expressedas

φ₁={(x ₀ ^((min))(C ₁₀), c ₁₀), (x ₀ ^((min))(c₁₁), c₁₁), . . . , (x ₀^((min))(c _(1m1-1)), c _(1m1-1))}

The first candidate group 100 ₁ contains the same number of candidatesas the number, m₁, of values that can be taken in the modulation schemeapplied to the transmitted signal x₁.

Similarly to the first candidate group setting unit 431, the secondcandidate group setting unit 432 obtains a set of candidates for thelikely transmitted signals by using the unitary transformed vector z′and upper triangular matrix R′ calculated based on the channel matrixH′. Referring to equation (9), it is seen that the element z′₀ in theunitary transformed vector contains the components of both transmittedsignals x₀ and x₁. Therefore, based on equation (9), the secondcandidate group setting unit 432 obtains as an estimate of thetransmitted signal x₁ the residual component calculated by canceling thecomponent of the transmitted signal x₀ from the unitary transformedsignal z′₀. Then, the second candidate group setting unit 432 obtains apair made up of a given candidate c_(0i) for the transmitted signal x₀and the value that is closest, among the values that the transmittedsignal x₁ can take, to the estimate of the transmitted signal x₁ whenthe transmitted signal x₀ is represented by that given candidate, andsets this pair as the transmitted signal candidate set.

When the transmitted signal x₀ is a symbol replica c_(0i) (i=0, 1, . . ., m₀₋₁), the estimate u_(1i) of the transmitted signal x₁ is expressedby the following equation. Here, c_(0i) is a symbol replica of thetransmitted signal x₀. On the other hand, m₀ represents the number ofvalues that can be taken in the modulation scheme applied to thetransmitted signal x₀.

$\begin{matrix}{u_{1i} = \frac{z_{0}^{\prime} - {r_{- 1}^{\prime}c_{0i}}}{r_{00}^{\prime}}} & (11)\end{matrix}$

Similarly to the first candidate group setting unit 431, the secondcandidate group setting unit 432 repeats the process for detecting thequadrant to which the estimate u_(1i) belongs, and determines the signalvalue of the symbol closest to the estimate u_(1i) as being thecandidate for the transmitted signal x₁ when the transmitted signal x₀is represented by c_(0i). In the following, the candidate for thetransmitted signal x₁ when the transmitted signal x₀ is c_(0i) isdenoted by x_(i) ^((min))(c_(0i)). Then, by determining the candidatefor the transmitted signal x₁ for each symbol replica c_(0i) (i=0, 1, .. . , m₁-1), the second candidate group setting unit 432 obtains asecond candidate group φ2 which is a collection of candidate sets forthe transmitted signals x₀ and x₁. Here, the second candidate group φ2is expressed as

φ₂={(c ₀₀ , x ₁ ^((min)), (c ₀₀)), (c ₀₁ , x ₁ ^((min)), (c ₀₁)), . . ., (c _(0m0-1) , x ₁ ^((min)), (c _(0m0-1)))}

The candidate group setting unit 43 passes the first and secondcandidate groups φ₁ and φ₂ to the common group searching unit 44 and theadditional metric calculating unit 47.

The common group searching unit 44 searches for the candidate sets ofthe transmitted signals x₀ and x₁ that are common to the first andsecond candidate groups φ₁ and φ₂. The first and second candidate groupsφ₁ and φ₂ are each a collection of candidate sets for the transmittedsignals x₀ and x₁ and are obtained in accordance with differentmathematical relations based on the same channel matrix. As a result, itis highly likely that the actually transmitted signal set is containedin both of the candidate groups. In view of this, the common groupsearching unit 44 searches for the transmitted signal candidate setsthat are contained in both of the two candidate groups and, using thesecandidate sets, constructs a common group on which metric calculationsare to be performed.

FIG. 4 is a conceptual diagram illustrating the first and secondcandidate groups φ₁ and φ₂ and the candidate sets of the transmittedsignals x₀ and x₁ that are common to the two groups. As an example, inFIG. 4, both of the transmitted signals x₀ and x₁ are signals modulatedby 64-QAM.

In FIG. 4, the first and second candidate groups φ₁ and φ₂ each containm transmitted signal candidate sets. Of these candidate sets, thecandidate set 401 in the first candidate group φ₁ and the candidate set411 in the second candidate group φ₂ both contain “010001” as thetransmitted signal x₀ and “010100” as the transmitted signal x₁.Therefore, the common group searching unit 44 selects (“010001”,“010100”) as the transmitted signal candidate set for the transmittedsignals (x₀, x₁). Further, the candidate set 402 in the first candidategroup φ₁ and the candidate set 412 in the second candidate group φ₂ bothcontain “111010” as the transmitted signal x₀ and “000101” as thetransmitted signal x₁. Therefore, the common group searching unit 44also selects (“111010”, “000101”) as the transmitted signal candidateset for the transmitted signals (x₀, x₁). The common group searchingunit 44 passes the thus constructed common group to the metriccalculating unit 45.

The number of transmitted signal candidate sets contained in the commongroup varies between 1 at minimum and min(m₀,m₁) at maximum, dependingon channel variation or noise. Here, m₀ and m₁ each represent the numberof values that the transmitted signal x₀ or x₁, respectively, can takein the modulation scheme applied to the transmitted signals x₀ and x₁.The function min(a,b) is a function that outputs a or b, whichever issmaller in value. Noting the estimate u_(0i), the earlier given equation(10) can be rewritten as

$\begin{matrix}{u_{0i} = {\frac{z_{0} - {r_{01}c_{1i}}}{r_{00}} = {\frac{z_{0}}{r_{00}} - {{\frac{r_{01}}{r_{00}} \cdot \frac{r_{01}}{r_{01}}}c_{1i}}}}} & (12)\end{matrix}$

As can be seen from equation (12), the estimate u_(0i) corresponds to asignal point that is obtained by rotating c_(1i) by an amount equal tothe phase arg(r₀₁) of the average power |r₀₁/r₀₀|² centered at a pointz₀/r₀₀. When the average power |r₀₁/r₀₀|² is small, i.e., when theinterference of the transmitted signal x₁ to the transmitted signal x₀is small, the estimate u_(0i) is located near the point z₀/r₀₀,regardless of the value of c_(1i). As a result, the number of candidatesfor the transmitted signal x₀ is small. On the other hand, when theaverage power |r₀₁/r₀₀|² is large, i.e., when the interference of thetransmitted signal x₁ to the transmitted signal x₀ is large, theestimate u_(0i) varies greatly, depending on c_(1i). As a result, thenumber of candidates for the transmitted signal x₀ increases.

Similarly, the estimate u_(1i) corresponds to a signal point that isobtained by rotating c_(0i) by an amount equal to the phase arg(r′₀₁) ofthe average power |r′₀₁/r′₀₀|² centered at a point z′₀/r′₀₀.Accordingly, as the average power |r′₀₁/r′₀₀|² decreases, i.e., as theinterference of the transmitted signal x₀ to the transmitted signal x₁decreases, the number of candidates for the transmitted signal x₁decreases. In this way, as the interference of one transmitted signal tothe other transmitted signal decreases, the number of transmitted signalcandidates decreases. More specifically, as the interference of onetransmitted signal to the other transmitted signal decreases, thereceiving apparatus 3 can further reduce the amount of computationneeded to demultiplex the transmitted signals.

For each transmitted signal candidate set contained in the common group,the metric calculating unit 45 calculates a metric that indicates ameasure of the likelihood of the transmitted signal candidate setrepresenting the actually transmitted signal set. The metric indicatesthe distance between the actually received signals and the receivedsignals estimated by assuming that one particular transmitted signalcandidate set represents the actually transmitted signal set. Forexample, the metric calculating unit 45 calculates the metric d_(j) asshown in the following equation by taking the sum of the squaredEuclidian distances calculated between the unitary transformed signalsz₀ and z₁ and the estimated received signals obtained by substitutingeach transmitted signal candidate set (c_(0j), c_(1j)) (j=0, 1, . . . ,k-1) into the first term on the right-hand side of equation (7).

d _(j) =z ₁ −r ₁₁ c _(1j)|² +z ₀ −r ₀₁ c _(ij) −r ₀₀ c _(0j)|²   (13)

Here, k indicates the total number of transmitted signal candidate setscontained in the common group. The metric calculating unit 45 may useequation (9) instead of equation (7).

Alternatively, the metric calculating unit 45 may calculate the metricd_(j) as shown in the following equation by calculating the Manhattandistance between the unitary transformed signals z₀ and z₁ and theestimated received signals obtained by substituting each transmittedsignal candidate set (c_(0j), c_(1j)) into the first term on theright-hand side of equation (7).

d _(i) =|Re(z ₁ −r ₁₁ c _(1j))|+|Im(z ₁ −r ₁₁ c _(1j))|+|Re(z ₀ −r ₀₁ c_(1j) −r ₀₀ c _(0j))|+|Im(z ₀ −r ₀₁ c _(1j) −r ₀₀ c _(0j))|  (14)

The function Re(α) is a function that outputs the real component of avariable u, and the function Im(α) is a function that outputs theimaginary component of the variable α. Further, the metric calculatingunit 45 may calculate as the metric some other measure that indicatesthe distance between the unitary transformed signals z₀ and z₁ and thetransmitted signal candidate set (c_(0j) , c _(1j)).

The metric calculating unit 45 passes each transmitted signal candidateset contained in the common group and its metric d_(j) to the minimumvalue searching unit 46.

The minimum value searching unit 46 is an example of a transmittedsignal estimator, and finds the minimum value among the metrics d_(j)calculated for the transmitted signal candidates. The minimum valuesearching unit 46 then assumes that the transmitted signal candidate set(c_(0min), c_(1min)) corresponding to the minimum value d_(min) of themetrics d_(j) represents the actually transmitted signal set (x₀, x₁).Hereinafter, the transmitted signal candidate set (c_(0min), c_(1min))assumed to be the actually transmitted signal set (x₀, x₁) is referredto as the most likely symbol set, and the symbols (x₀ ^((ML)), x₁^((ML))) corresponding to the symbol replicas contained as thetransmitted signal candidates in the most likely symbol set are calledthe most likely symbols.

The minimum value searching unit 46 passes the minimum value d_(min) andthe most likely symbol set (c_(0min), c_(1min)) to the logarithmiclikelihood ratio computing unit 48. Further, the minimum value searchingunit 46 passes each transmitted signal candidate set and the metricd_(j) calculated for each candidate set to the additional metriccalculating unit 47.

For each of the most likely symbols, the additional metric calculatingunit 47 detects, from among the symbols defined by inverting any one ofthe bits of the most likely symbol, any symbol that is located within aprescribed distance of the most likely symbol, and identifies such asymbol as an inverted bit symbol. Then, for the symbol replica x_(0p)corresponding to the inverted bit symbol s_(0p) (p=1, 2, . . . , m)obtained for the transmitted signal x₀, the additional metriccalculating unit 47 identifies the symbol replica x₁ ^((min))(x_(0p)) ofthe transmitted signal x₁ that corresponds to the symbol replica x_(0p).For example, the additional metric calculating unit 47 detects acandidate set containing the symbol replica x_(0p) from among thetransmitted signal candidate sets contained in the second candidategroup φ₂. Then, based on the detected transmitted signal candidate set,the additional metric calculating unit 47 identifies the symbol replicax₁ ^((min)) (x_(0p)) of the transmitted signal x₁ that corresponds tothe symbol replica x_(0p). Similarly, for the symbol replica x_(1p)corresponding to the inverted bit symbol s_(1p) obtained for thetransmitted signal x₁, the additional metric calculating unit 47identifies the symbol replica x₀ ^((min))(x_(1p)) of the transmittedsignal x₀ that corresponds to the symbol replica x_(1p) by referring tothe first candidate group φ₁.

The additional metric calculating unit 47 calculates an additionalmetric d^((additional)) between the unitary transformed signals z₀ andz₁ and the symbol replica set (x_(0p), x₁ ^((min)) (x_(0p))) associatedwith the inverted bit symbol s_(0r) obtained for the transmitted signalx₀. Similarly, the additional metric calculating unit 47 calculates anadditional metric d^((additional)) between the unitary transformedsignals z₀ and z₁ and the symbol replica set (x₀ ^((min)) (x_(1p)),x_(1p)) associated with the inverted bit symbol s_(1r) obtained for thetransmitted signal x₁. The additional metric calculating unit 47 cancalculate these additional metrics, for example, in accordance withequation (13) or (14). The additional metrics are used to compute thelogarithmic likelihood ratio that the decoding unit 36 uses whenperforming error-correction decoding. Therefore, the additional metriccalculating unit 47 passes the additional metric obtained for eachinverted bit symbol to the logarithmic likelihood ratio computing unit48.

If the metric d has already been calculated by the metric calculatingunit 45 for one of the symbol replica sets (x₀ ^((min)) (x_(1p)),x_(1p)) and (x_(0p), x₁ ^((min)) (x_(0p))), the additional metriccalculating unit 47 passes that metric d to the logarithmic likelihoodratio computing unit 48.

FIG. 5 is a diagram depicting the inverted bit symbols when, for eachinverted bit, the closest symbol is selected as the inverted bit symbol,for example, for the case where the transmitted signal x₀ is modulatedby 64-QAM and where the most likely symbol corresponding to thetransmitted signal x₀ is “000000”. As depicted in FIG. 5, the symbolslocated in blocks 501 to 506 are selected as the inverted bit symbols.For example, when the inverted bit is the rightmost bit, the symbol“000001” in block 501 is closest to the most likely bit. Therefore,“000001” is selected as the inverted bit symbol. On the other hand, whenthe inverted bit is the leftmost bit, the symbol “100010” in block 506,which is closest to the most likely symbol among the symbols whoseleftmost bit is “1”, is selected as the inverted bit symbol.

FIG. 6 is a diagram depicting the inverted bit symbols when, for eachinverted bit, the closest symbol and the second closest symbol areselected as the inverted bit symbols for the case where the most likelysymbol corresponding to the transmitted signal x₀ is “000000”. Asdepicted in FIG. 6, the symbols located in blocks 601 to 614 areselected as the inverted bit symbols.

Since the position of the signal point corresponding to each symbol ispredetermined, the inverted bit symbols for each most likely symbol canbe determined in advance. Therefore, a reference table defining thecorresponding inverted bit symbols for each most likely symbol may bestored in advance in a memory circuit incorporated in the additionalmetric calculating unit 47. The additional metric calculating unit 47can then identify the inverted bit symbols corresponding to each mostlikely symbol by referring to the reference table.

The logarithmic likelihood ratio computing unit 48 computes thelogarithmic likelihood ratio (LLR) for each bit. The logarithmiclikelihood ratio computing unit 48 computes in accordance with thefollowing equation the bit LLR_(r)(n) which is the LLR for the n-th bitfrom the left of the transmitted signal x_(r).

$\begin{matrix}{\mspace{20mu} {{{{{{LLR}_{r}(n)} = {\sqrt{d_{r,{m\; i\; n}}\left( {b_{n} = 1} \right)} - \sqrt{d_{r,{m\; i\; n}}\left( {b_{n} = 0} \right)}}}\mspace{20mu} {d_{r,{m\; i\; n}}\left( {b_{n} = {{bit}\left( {x_{r}^{({ML})},n} \right)}} \right)}} = {d_{m\; i\; n} = {d\left( {x_{0}^{({ML})},x_{1}^{({ML})}} \right)}}}{{d_{r,{m\; i\; n}}\left( {b_{n} = {{invbit}\left( {x_{r}^{({ML})},n} \right)}} \right)} = {\min \begin{bmatrix}{\min\limits_{{{bit}{({c_{rj}^{({common})},n})}} = {{invbit}{({x_{r}^{({ML})},n})}}}\left\{ {d\left( {c_{0j}^{({common})},c_{1j}^{({common})}} \right)} \right\}} \\{\min\limits_{{{bit}{({x_{0p}^{({inv})},n})}} = {{invbit}{({x_{0}^{({ML})},n})}}}\left\{ {d^{({additional})}\left( {x_{0p}^{({inv})},{x_{1}^{({m\; i\; n})}\left( x_{0p}^{({inv})} \right)}} \right)} \right\}} \\{\min\limits_{{{bit}{({x_{1p}^{({inv})},n})}} = {{invbit}{({x_{1}^{({ML})},n})}}}\left\{ {d^{({additional})}\left( {{x_{0}^{({m\; i\; n})}\left( x_{1p}^{({inv})} \right)},x_{1p}^{({inv})}} \right)} \right\}}\end{bmatrix}}}}} & (15)\end{matrix}$

where d_(min) is the metric calculated for the most likely symbol set(x₀ ^((ML)), x₁ ^((ML))). The function bit (x_(r) ^((ML)), n) indicatesthe value of the n-th bit from the left of the most likely symbol x_(r)^((ML)) (r=0, 1). On the other hand, the function invbit (x_(r) ^((ML)),n) indicates the inverted value of the n-th bit from the left of themost likely symbol x_(r) ^((ML)) (r=0, 1). The function min_(a-b) (d) isa function that outputs a minimum value selected from among the metricsd that satisfy the condition a=b. Further, d(c_(0j) ^((common)), c_(1j)^((common))) (j=0, 1, . . . , k-1) is the metric calculated for thetransmitted signal candidate set (c_(0j) ^((common)), c_(1j)^((common))) contained in the common group. On the other hand,d^((additional)) (x_(0p) ^((inv)), x_(1p) ^((min)) ( x_(0p) ^((inv))) isthe additional metric calculated for a pair made up of the inverted bitsymbol x_(0p) ^((inv)) of the most likely symbol x₀ ^((ML)) and thesymbol x_(1p) ^((min)) (x_(0p) ^((inv))) corresponding to that invertedbit symbol. Likewise, d^((additional)) (x_(0p) ^((min)) (x_(1p)^((inv)), x_(1p) ^((inv)) is the additional metric calculated for a pairmade up of the inverted bit symbol x_(1p) ^((inv)) of the most likelysymbol x₁ ^((ML)) and the symbol x_(0p) ^((min)) (x_(1p) ^((inv)))corresponding to that inverted bit symbol.

Alternatively, the logarithmic likelihood ratio computing unit 48 maycompute the bit LLR_(r)(n) in accordance with the following equation.

LLR _(r)(n)=d _(r,min)(b _(n)=1)−d _(r,min)(b _(n)=0)   (16)

The logarithmic likelihood ratio computing unit 48 passes each bitLLR_(R)(n) and its corresponding inverted bit symbols to the decodingunit 36.

If the logarithmic likelihood ratio is not used in the error-correctiondecoding process performed by the decoding unit 36, the additionalmetric calculating unit 47 and the logarithmic likelihood ratiocomputing unit 48 may be omitted.

FIGS. 7A and 7B and FIG. 8 are operation flowcharts illustrating thetransmitted signal demultiplexing process. The transmitted signaldemultiplexing process is performed under control of the streamdemultiplexer 35, and is initiated each time the receiving apparatus 3receives a signal.

The first QR-decomposition unit 421 in the QR-decomposition unit 42QR-decomposes the channel matrix H into the unitary matrix Q and theupper triangular matrix R (step S101). Then, the first QR-decompositionunit 421 generates the unitary transformed vector z (=(z₀, z₁)) of thereceived signal vector Y by multiplying the received signal vector Y bythe Hermitian conjugate Q^(H) of the unitary matrix Q (step S102). Thefirst QR-decomposition unit 421 passes the unitary transformed vector zand the upper triangular matrix R to the candidate group setting unit43.

For the particular transmitted signal x₀, the first candidate groupsetting unit 431 in the candidate group setting unit 43 calculates theresidual component by canceling the component relating to the symbolreplica c_(1i) of the other transmitted signal x₁ from the unitarytransformed signal z₀ and thus calculates the estimate u_(0i) of thatparticular transmitted signal x₀ (step S103). Here, the first candidategroup setting unit 431 calculates the estimate u_(0i) for each symbolreplica c_(1i) (i=0, 1, 2, . . . , m₁-1). Then, the first candidategroup setting unit 431 generates a first candidate group of transmittedsignal candidate sets, each designated as (x₀ ^((min)) (c_(1i)), c_(1i))and made up of the symbol replica x₀ ^((min)) (c_(1i)) closest to theestimate u_(0i) and the corresponding symbol replica c_(1i) of thetransmitted signal x₁ (step S104). The first candidate group settingunit 431 passes the first candidate group to the common group searchingunit 44 and the additional metric calculating unit 47.

As illustrated in FIG. 7B, the channel interchanging unit 41 creates thetransformed channel matrix H′ by interchanging the order of the columnsin the channel matrix H (step S105). Then, the channel interchangingunit 41 passes the transformed channel matrix H′ to the QR-decompositionunit 42.

The second QR-decomposition unit 422 in the QR-decomposition unit 42QR-decomposes the transformed channel matrix H′ into the unitary matrixQ′ and the upper triangular matrix R′ (step S106). Then, the secondQR-decomposition unit 422 generates the unitary transformed vector z′(=(z′₀, z′₁)) of the received signal vector Y by multiplying thereceived signal vector Y by the Hermitian conjugate Q′^(H) of theunitary matrix Q′ (step S107). The second QR-decomposition unit 422passes the unitary transformed vector z′ and the upper triangular matrixR′ to the candidate group setting unit 43.

For the particular transmitted signal x₁, the second candidate groupsetting unit 432 in the candidate group setting unit 43 calculates theresidual component by canceling the component relating to the symbolreplica c_(0i) of the other transmitted signal x₀ from the unitarytransformed signal z′₀ and thus calculates the estimate u_(1i) of thatparticular transmitted signal x₁ (step S108). The second candidate groupsetting unit 432 calculates the estimate u_(1i) for each symbol replicac_(0i) (i=0, 1, 2, . . . , m₀-1). Then, the second candidate groupsetting unit 432 generates a second candidate group of transmittedsignal candidate sets, each designated as (c_(0i), x_(i) ^((min))(c_(0i))) and made up of the symbol replica x₁ ^((min)) (c_(0i)) closestto the estimate u_(1i) and the corresponding symbol replica c_(0i) ofthe transmitted signal x₀ (step S109). The second candidate groupsetting unit 432 passes the second candidate group to the common groupsearching unit 44 and the additional metric calculating unit 47.

The common group searching unit 44 searches for the transmitted signalcandidate sets that are common between the first and second candidategroups (step S110). The common group searching unit 44 passes the commongroup containing the common transmitted signal candidate sets to themetric calculating unit 45.

As illustrated in FIG. 8, for each transmitted signal candidate setcontained in the common group, the metric calculating unit 45 calculatesthe metric for evaluating the distance between the received signal setand the estimated received signal set obtained based on the transmittedsignal candidate set (step S111).

The minimum value searching unit 46 estimates that the transmittedsignal candidates contained in the candidate set corresponding to theminimum metric value represent the actually transmitted signals (stepS112). The minimum value searching unit 46 passes the minimum metricvalue and the estimated transmitted signals to the logarithmiclikelihood ratio computing unit 48. The minimum value searching unit 46also passes the estimated transmitted signals to the additional metriccalculating unit 47.

From among the symbols having inverted bits with respect to each mostlikely symbol, the additional metric calculating unit 47 selects asinverted bit symbols those symbols that are located within a prescribeddistance of the most likely symbol (step S113). Then, the additionalmetric calculating unit 47 determines the symbol replica setscorresponding to the inverted bit symbols by referring to the first andsecond candidate groups (step S114). The additional metric calculatingunit 47 calculates the metric for each inverted bit symbol (step S115).The additional metric calculating unit 47 passes the metrics and theinverted bit symbols to the logarithmic likelihood ratio computing unit48.

The logarithmic likelihood ratio computing unit 48 computes thelogarithmic likelihood ratio for each inverted bit of each most likelysymbol by calculating the difference between the square root of theminimum metric and the square root of the minimum value of the metriccorresponding to the inverted bit symbol (step S116). Then, thelogarithmic likelihood ratio computing unit 48 outputs the estimatedtransmitted signal, the logarithmic likelihood ratio, and the invertedbit symbol used for the computation of the logarithmic likelihood ratio.

After that, the stream demultiplexer 35 terminates the transmittedsignal demultiplexing process. The stream demultiplexer 35 may performthe process from step S101 to step S104 in parallel with the processfrom step S105 to step S109.

Table 1 provides a comparison between the number of metric calculationsperformed in the transmitted signal demultiplexing process according tothe present embodiment and the number of metric calculations performedin the transmitted signal demultiplexing process according to the priorart, for the case where the two transmitted signals are both modulatedby 64-QAM. In Table 1, it is assumed that the metric is calculated asthe squared Euclidian distance in accordance with equation (13), andthat one norm calculation equals one metric calculation. It is alsoassumed that the additional metric calculating unit 47 calculates themetric by selecting only the symbol closest to the most likely symbol asthe inverted bit symbol for each inverted bit from among the symbolscontaining that inverted bit.

TABLE 1 COMPARISON OF NUMBER OF METRIC CALCULATIONS BETWEEN VARIOUSMETHODS NUMBER OF METRIC METHOD OF RECEPTION CALCULATIONS METHOD OFPRESENT EMBODIMENT 26-128 QRM-MLD METHOD 4160  ASESS METHOD 128 LORDMETHOD 256

According to the method of the present embodiment, the number of metriccalculations is 26 at minimum and 128 at maximum. When there is only onetransmitted signal candidate set that is common between the first andsecond candidate groups, the number of metric calculations becomesminimum. In this case, two metric calculations are performed for thatcommon candidate set and, since there are log₂₆₄ (=6) inverted bitsymbols for each transmitted signal, 24 metric calculations areperformed for the inverted bit symbols.

On the other hand, when there are 64 transmitted signal candidate setsthat are common between the first and second candidate groups, that is,when the two candidate groups are equal, the number of metriccalculations becomes maximum. In this case, 128 (=2×64) metriccalculations are performed for the common candidate sets. The number ofmetric calculations for the inverted bit symbols is 0, since thetransmitted signal sets containing the inverted bit symbols arecontained in the common group.

As can be seen from Table 1, even when the number of metric calculationsis maximum, the number of metric calculations according to the method ofthe present embodiment is smaller than the number of metric calculationsaccording to any prior art transmitted signal demultiplexing method.

As has been described above, when demultiplexing the transmittedsignals, the receiving apparatus according to the first embodimentobtains two channel matrices by interchanging the order of the channelsbetween them. Then, the receiving apparatus obtains sets of transmittedsignal candidates for each channel matrix. For each particulartransmitted signal, the receiving apparatus determines the transmittedsignal candidate by selecting the symbol replica that is closest to theresidual component calculated by canceling the component correspondingto the other transmitted signal candidate from the unitary transformedsignal of the received signal having components relating to all of thetransmitted signals. The receiving apparatus estimates the transmittedsignals by calculating the metrics only for the candidate sets common tothe two groups of transmitted signal candidate sets obtained for the twochannel matrices. In this way, since the receiving apparatus candetermine each transmitted signal candidate set without calculating themetric that involves a large amount of computation, the number of metriccalculations can be reduced. As a result, the receiving apparatus canreduce the amount of computation when demultiplexing the transmittedsignals.

Next, a receiving apparatus according to a second embodiment will bedescribed. When performing the transmitted signal demultiplexingprocess, the receiving apparatus according to the second embodimentallocates priorities to the transmitted signal candidate sets that arecommon between the first and second candidate groups, and calculates themetrics only for high priority candidate sets. The only differencebetween the receiving apparatus according to the second embodiment andthe receiving apparatus according to the first embodiment lies in thestream demultiplexer. Therefore, the following description deals onlywith the stream multiplexer.

FIG. 9 is a diagram schematically illustrating the configuration of thestream demultiplexer 351 in the receiving apparatus according to thesecond embodiment. The stream demultiplexer 351 includes a channelinterchanging unit 41, a QR-decomposition unit 42, a candidate groupsetting unit 43, a common group searching unit 44, a metric calculatingunit 45, a minimum value searching unit 46, an additional metriccalculating unit 47, a logarithmic likelihood ratio computing unit 48,and a ranking unit 51.

These units constituting the stream demultiplexer 351 may be implementedas separate computing circuits. Alternatively, these units constitutingthe stream demultiplexer 351 may be integrated into a single computingcircuit implementing the functions of the respective units.

In FIG. 9, the units constituting the stream demultiplexer 351 aredesignated by the same reference numerals as those used to designate thecorresponding component elements of the stream demultiplexer 35according to the first embodiment depicted in FIG. 2. The streamdemultiplexer 351 differs from the stream demultiplexer 35 according tothe first embodiment by the inclusion of the ranking unit 51.

The ranking unit 51 includes a first signal ranking unit 511 and asecond signal ranking unit 512.

The first signal ranking unit 511 calculates ranking values forprioritizing the transmitted signal candidate sets contained in thefirst candidate group. As shown in equation (7) defining therelationship between the unitary transformed vector z, the uppertriangular matrix R, and the transmitted signal vector X, thetransmitted signal x₁ is expressed as shown in the following equation byusing the unitary transformed vector z₁.

$\begin{matrix}{x_{1} = {\frac{Z_{1}}{r_{11}} - \frac{{q_{01}^{*}n_{0}} + {q_{11}^{*}n_{1}}}{r_{11}}}} & (17)\end{matrix}$

The first term (z₁/r₁₁) on the right-hand side of equation (17)indicates the estimate v₁ of the transmitted signal x₁.

That is, if the noise component is small, then the closer to theestimate v₁ the signal value is, the more likely that the signal valuerepresents the actually transmitted signal x₁.

Therefore, the first signal ranking unit 511 determines the rankingvalue according to the closeness to the estimate v₁ for each of thesymbol replicas c_(1i) corresponding to the signal values that thetransmitted signal x₁ can take. For example, the first signal rankingunit 511 assigns a smaller ranking value to a signal value closer to theestimate v₁. The ranking value is a measure of the likelihood that thesignal value represents the transmitted signal x₁. In the illustratedexample, the smaller the ranking value, the greater the likelihood.

To determine the ranking value, the first signal ranking unit 511detects the quadrant to which the estimate v₁ (=z₁/r₁₁) of thetransmitted signal x₁ belongs in a coordinate system that defines the Iand Q signals representing the signal values that the transmitted signalx₁ can take. Then, the first signal ranking unit 511 determines howclose to the estimate v₁ each signal value is, by performing thequadrant detection iteratively a number ((1/2)log₂m₁) of times, eachtime by setting its origin at the center of the quadrant to which theestimate v₁ belongs. Here, m₁ represents the number of values that canbe taken in the modulation scheme applied to the transmitted signal x₁;for example, when the modulation scheme is QPSK, m₁=2.

FIGS. 10A and 10B are diagrams depicting an example of the positionalrelationship between the estimate v₁ of the transmitted signal x₁ andthe values that the transmitted signal x₁ can take. As an example, it isassumed that the modulation scheme applied to the transmitted signal x₁is QPSK. In FIGS. 10A and 10B, the abscissa represents the I signalcomponent, and the ordinate represents the Q signal component. Points1001 a to 1001 d are the signal points corresponding to the signalvalues that the transmitted signal x₁ can take. For example, point 1001a represents the signal value corresponding to the symbol “00”. On theother hand, point 1010 indicates the estimate v₁. In the illustratedexample, the I and Q signal components of the estimate v₁ are bothpositive values. As can be seen, of the four signal values, the signalvalue corresponding to the symbol “00” is closest to the estimate v₁. Onthe other hand, the signal value corresponding to the symbol “11”, whoseI and Q components are both different from those of the estimate v₁, isfarthest from the estimate v₁. Therefore, the first signal ranking unit511 assigns, for example, a ranking value “1” to the symbol replicacorresponding to the symbol “00” and a ranking value “4” to the symbolreplica corresponding to the symbol “11”. As for the symbol replicacorresponding to the symbol “01” and the signal value corresponding tothe symbol “10”, it is not yet known, at the end of the first quadrantdetection, which signal value is closer to the estimate v₁. Therefore,the first signal ranking unit 511 assigns a ranking value “2” to boththe symbol replica corresponding to the symbol “01” and the symbolreplica corresponding to the symbol “10”.

The first signal ranking unit 511 may perform the quadrant detectioniteratively more than ((1/2)log₂m₁) times. The first signal ranking unit511 can then determine the order of closeness to the estimate v₁ for allthe signal values.

For example, as depicted in FIG. 10B, by performing the second quadrantdetection on the estimate v₁, it can be seen that the estimate v₁ islocated in a region 1020 which is one of 16 regions. The region 1020 isnearer to the signal value corresponding to the symbol “01” than to thesignal value corresponding to the symbol “10”. Accordingly, the firstsignal ranking unit 511 can determine that the signal valuecorresponding to the symbol “01” is closer to the estimate v₁ than thesignal value corresponding to the symbol “10” is. Therefore, the firstsignal ranking unit 511 assigns the ranking values “1”, “2”, “3”, and“4”, respectively, to the symbol replicas corresponding to therespective symbols “00”, “01”, “10”, and “11”.

The second signal ranking unit 512 calculates ranking values for rankingthe transmitted signal candidate sets contained in the second candidategroup.

Here, the second signal ranking unit 512, similarly to the first signalranking unit 511, calculates (z′₁/r′₁₁) based on equation (9) and takesit as the estimate v₀ of the transmitted signal x₀. Then, by detectingthe quadrant to which the estimate v₀ belongs, the second signal rankingunit 512 determines the ranking value according to the closeness to theestimate v₀ for each of the symbol replicas c_(0i) corresponding to thesignal values that the transmitted signal x₀ can take.

The ranking unit 51 passes to the candidate group setting unit 43 theranking value R_(0i) assigned to each of the symbol replicas c_(0i)corresponding to the signal values that the transmitted signal x₀ cantake and the ranking value R_(1i) assigned to each of the symbolreplicas c_(1i) corresponding to the signal values that the transmittedsignal x₁ can take.

The candidate group setting unit 43, similarly to the candidate groupsetting unit 43 in the first embodiment, obtains the first and secondcandidate groups each made up of sets of candidates for the transmittedsignals x₀ and x₁.

The first candidate group setting unit 431 receives the ranking valueR_(1i) assigned to the symbol replica c_(1i) contained in each of thetransmitted signal candidate sets in the first candidate group, andtakes it as the ranking value that indicates the degree of likelihood ofthat candidate set representing the actually transmitted signal set.Likewise, the second candidate group setting unit 432 receives theranking value R_(0i) assigned to the symbol replica c_(0i) contained ineach of the transmitted signal candidate sets in the second candidategroup, and takes it as the ranking value that indicates the degree oflikelihood of that candidate set representing the actually transmittedsignal set.

The candidate group setting unit 43 passes the first and secondcandidate groups and the ranking values of the candidate sets containedin the respective candidate groups to the additional metric calculatingunit 47.

The common group searching unit 44 searches for the transmitted signalcandidate sets that are common between the first and second candidategroups, and constructs a common group using these common transmittedsignal candidate sets. Then, the common group searching unit 44allocates priorities according to the ranking values (R_(0i) and R_(1i))assigned to the common transmitted signal candidate sets.

For example, the common group searching unit 44 allocates priority toeach common transmitted signal candidate set by calculating the sumR_(sum) of the ranking values (=R_(0i)+R_(1i)). Then, the common groupsearching unit 44 selects a number, S, of candidate sets in decreasingorder of priority, i.e., in increasing order of the sum R_(sum) of theranking values.

Alternatively, the common group searching unit 44 may allocate priorityto each common transmitted signal candidate set by calculating theproduct R_(pro) of the ranking values (=R_(0i)* R_(1i)). Then, thecommon group searching unit 44 may select a number, S, of candidate setsin increasing order of the product R_(pro) of the ranking values.

If the number of transmitted signal candidate sets contained in thecommon group is smaller than S, the common group searching unit 44selects all of the transmitted signal candidate sets contained in thecommon group. Here, S is an integer not smaller than 1, and is chosen tobe smaller than m₀ or m₁, whichever is smaller, which represents thenumber of values that can be taken in the modulation scheme applied tothe transmitted signal x₀ or x₁. For example, when the modulation schemeapplied to the transmitted signal x₀ or x₁ is 64-QAM, S is set, forexample, to 16.

The common group searching unit 44 passes the selected transmittedsignal candidate sets to the metric calculating unit 45. The metriccalculating unit 45 calculates the metrics only for the transmittedsignal candidate sets selected by the common group searching unit 44.

FIGS. 11A and 11B are an operation flowchart illustrating thetransmitted signal demultiplexing process according to the secondembodiment, which is performed instead of the transmitted signaldemultiplexing process of steps S101 to S110 illustrated in FIGS. 7A and7B. The transmitted signal demultiplexing process is performed undercontrol of the stream demultiplexer 351, and is initiated each time thereceiving apparatus 3 receives a signal.

The first QR-decomposition unit 421 in the QR-decomposition unit 42QR-decomposes the channel matrix H into the unitary matrix Q and theupper triangular matrix R (step S201). Then, the first QR-decompositionunit 421 generates the unitary transformed vector z (=(z₀, z₁)) of thereceived signal vector Y by multiplying the received signal vector Y bythe Hermitian conjugate Q^(H) of the unitary matrix Q (step S202). Thefirst QR-decomposition unit 421 passes the unitary transformed vector zand the upper triangular matrix R to the ranking unit 51 and thecandidate group setting unit 43.

The first signal ranking unit 511 in the ranking unit 51 determines theranking value R_(1i) according to the closeness to the estimate v₁(=z₁/r₁₁) of the transmitted signal x₁ for each of the symbol replicasc_(1i) representing the signal values that the transmitted signal x₁ cantake (step S203). Then, the first signal ranking unit 511 passes theranking value R_(1i) determined for each of the symbol replicas c_(1i)to the candidate group setting unit 43.

For the particular transmitted signal x₀, the first candidate groupsetting unit 431 in the candidate group setting unit 43 calculates theresidual component by canceling the component relating to the symbolreplica c_(1i) of the other transmitted signal x₁ from the unitarytransformed signal z₀ and thus calculates the estimate u_(0i) of thatparticular transmitted signal x₀ (step S204). The first candidate groupsetting unit 431 calculates the estimate u_(0i) for each symbol replicac_(1i) (i=0, 1, 2, . . . , m₁-1). Then, the first candidate groupsetting unit 431 generates a first candidate group of transmitted signalcandidate sets, each designated as (x₀ ^((min)) (c_(1i)), c_(1i)) andmade up of the symbol replica x₀ ^((min)) (c_(1i)) closest to theestimate u_(0i) and the corresponding symbol replica c_(1i) of thatother transmitted signal x₁ (step S205). The first candidate groupsetting unit 431 receives the ranking value R_(1i) assigned to thesymbol replica c_(1i) contained in each of the transmitted signalcandidate sets in the first candidate group, and takes it as the rankingvalue for that candidate set. Then, the first candidate group settingunit 431 passes the first candidate group and the ranking values of therespective candidate sets contained in that group to the common groupsearching unit 44 and the additional metric calculating unit 47.

The channel interchanging unit 41 creates the transformed channel matrixH′ by interchanging the order of the columns in the channel matrix H(step S206). Then, the channel interchanging unit 41 passes thetransformed channel matrix H′ to the QR-decomposition unit 42.

As illustrated in FIG. 11B, the second QR-decomposition unit 422 in theQR-decomposition unit 42 QR-decomposes the transformed channel matrix H′into the unitary matrix Q′ and the upper triangular matrix R′ (stepS207). Then, the second QR-decomposition unit 422 generates the unitarytransformed vector z′ (=(z′₀, z′₁)) by multiplying the received signalvector Y by the Hermitian conjugate Q′^(H) of the unitary matrix Q′(step S208). The second QR-decomposition unit 422 passes the unitarytransformed vector z′ and the upper triangular matrix R′ to the rankingunit 51 and the candidate group setting unit 43.

The second signal ranking unit 512 in the ranking unit 51 determines theranking value R_(0i) according to the closeness to the estimate v₀(=z′₁/r′₁₁) of the transmitted signal x₀ for each of the symbol replicasc_(0i) representing the signal values that the transmitted signal x₀ cantake (step S209). Then, the second signal ranking unit 512 passes theranking value R_(0i) determined for each of the symbol replicas c_(0i)to the candidate group setting unit 43.

For the particular transmitted signal x₁, the second candidate groupsetting unit 432 calculates the residual component by canceling thecomponent relating to the symbol replica c_(0i) of the other transmittedsignal x₀ from the unitary transformed signal z′₀ and thus calculatesthe estimate u_(1i) of that particular transmitted signal x₁ (stepS210). The second candidate group setting unit 432 calculates theestimate u_(1i) for each symbol replica c_(0i) (i=0, 1, 2, . . . ,m₀-1). Then, the second candidate group setting unit 432 generates asecond candidate group of transmitted signal candidate sets, eachdesignated as (c_(0i), x₁ ^((min)) (c_(0i))) and made up of the symbolreplica x₁ ^((min)) (c_(0i)) closest to the estimate u_(1i) and thecorresponding symbol replica c_(0i) of that other transmitted signal x₀(step S211). The second candidate group setting unit 432 receives theranking value R_(0i) assigned to the symbol replica c_(0i) contained ineach of the transmitted signal candidate sets in the second candidategroup, and takes it as the ranking value for that candidate set. Then,the second candidate group setting unit 432 passes the second candidategroup and the ranking values of the respective candidate sets containedin that group to the common group searching unit 44 and the additionalmetric calculating unit 47.

The common group searching unit 44 searches for the transmitted signalcandidate sets that are common between the first and second candidategroups, and constructs a common group using the common transmittedsignal candidate sets (step S212). The common group searching unit 44allocates priorities to the transmitted signal candidate sets containedin the common group according to the ranking values (R_(0i) and R_(1i))assigned to the respective transmitted signal candidate sets. Then, thecommon group searching unit 44 selects a predetermined number ofcandidate sets in decreasing order of priority (step S213). The commongroup searching unit 44 passes the thus selected transmitted signalcandidate sets to the metric calculating unit 45.

After that, the stream demultiplexer 351 proceeds to perform the processstarting from step S111 illustrated in FIG. 8. The stream demultiplexer351 may perform the process from step S201 to step S205 in parallel withthe process from step S206 to step S211.

In the second embodiment, the maximum number of transmitted signalcandidates for which the metric is to be calculated is defined by thepredetermined number S. That is, the number of metric calculations inthe metric calculating unit 45 is 2 S at maximum. On the other hand, thenumber of metric calculations in the additional metric calculating unit47 is (log₂m₀+log₂m₁)×2 at maximum. Here, m₀ and m₁ each represent thenumber of values that can be taken in the modulation scheme applied tothe transmitted signal x₀ or x₁, respectively. Accordingly, the maximumnumber of metric calculations in the second embodiment is given as (2S+(log₂m₀+log₂m₁)×2). For example, if the conditions for computing thenumber of metric calculations are the same as those provided in Table 1,and if S is set to 16, then the maximum number of metric calculations is56. In this way, compared with the receiving apparatus according to thefirst embodiment, the receiving apparatus according to the secondembodiment can further reduce the maximum number of metric calculations.

As described above, if the ranking value of any one of the symbolreplicas c_(0i) and c_(1i) of the transmitted signals x₀ and x₁ islarge, the priority of the transmitted signal candidate set concerned islow, and as a result, the metric is not calculated for such a candidateset. It is therefore preferable to reduce the amount of computationneeded to obtain such a candidate set.

In view of the above, the first candidate group setting unit 431 maydetermine the transmitted signal candidate sets by performing thequadrant detection only on the symbol replicas c_(1i) whose rankingvalues calculated by the first ranking unit 51 fall within the Y₁highest ranks. Similarly, the second candidate group setting unit 432may determine the transmitted signal candidate sets by performing thequadrant detection only on the symbol replicas c_(0i) whose rankingvalues calculated by the second ranking unit 52 fall within the Y₀highest ranks.

Since this serves to reduce the number of times that the quadrantdetection is performed, the stream demultiplexer 351 can further reducethe total amount of computation in the transmitted signal demultiplexingprocess. For example, when the modulation scheme applied to thetransmitted signals x₀ and x₁ is 64-QAM, and when σ₀=Σ₁=32, the amountof computation in the quadrant detection process performed by thecandidate group setting unit 43 can be reduced by a factor of 2,compared with the first and second embodiments.

On the other hand, if the modulation scheme applied to the transmittedsignal x₀ differs from the modulation scheme applied to the transmittedsignal x₁, Y₀ and Σ₁ may be set to different values. For example, if themodulation scheme applied to the transmitted signal x₀ is 16-QAM, andthe modulation scheme applied to the transmitted signal x₁ is 64-QAM,then Σ₀ is set to 8, while Σ₁ is set to 32. Alternatively, the values ofΣ₀ and Σ₁ may be varied according to the modulation scheme applied tothe transmitted signals x₀ and x₁. For example, if the modulation schemeapplied is QPSK, Σ₀ and Σ₁ are each set to 3; if the modulation schemeapplied is 16-QAM, Σ₀ and Σ₁ are each set to 8; and if the modulationscheme applied is 64-QAM, Σ₀ and Σ₁ are each set to 32.

In the above modified example, since the transmitted signal candidatesets are not obtained for all of the values that the transmitted signalsx₀ and x₁ can take, there can occur cases where neither the firstcandidate group nor the second candidate group contains any transmittedsignal candidate sets corresponding to the inverted symbols. In view ofthis, if neither the first candidate group nor the second candidategroup contains any transmitted signal candidate sets corresponding tothe inverted symbols, the additional metric calculating unit 47determines the transmitted signal candidate sets containing the invertedsymbols by performing the same processing as the candidate group settingunit 43 does.

Next, a receiving apparatus according to a third embodiment will bedescribed. In the receiving apparatus according to the third embodiment,when performing the transmitted signal demultiplexing process, onecandidate group setting unit refers to the candidate group constructedby the other candidate group setting unit. Then, the one candidate groupsetting unit obtains the transmitted signal candidate sets only for thesymbol replicas corresponding to the transmitted signal candidatescontained in the candidate group referred to by it.

FIG. 12 is a diagram schematically illustrating the configuration of thestream demultiplexer 352 in the receiving apparatus according to thethird embodiment. The stream demultiplexer 352 includes a channelinterchanging unit 41, a QR-decomposition unit 42, a candidate groupsetting unit 43, a common group searching unit 44, a metric calculatingunit 45, a minimum value searching unit 46, an additional metriccalculating unit 47, and a logarithmic likelihood ratio computing unit48.

These units constituting the stream demultiplexer 352 may be implementedas separate computing circuits. Alternatively, these units constitutingthe stream demultiplexer 352 may be integrated into a single computingcircuit implementing the functions of the respective units.

In FIG. 12, the units constituting the stream demultiplexer 352 aredesignated by the same reference numerals as those used to designate thecorresponding component elements of the stream demultiplexer 35according to the first embodiment depicted in FIG. 2. The streamdemultiplexer 352 differs from the stream demultiplexer 35 according tothe first embodiment in that the second candidate group setting unit 432in the candidate group setting unit 43 refers to the first candidategroup constructed by the first candidate group setting unit 431.

The second candidate group setting unit 432 refers to each transmittedsignal candidate set (x₀ ^((min))(c_(1i)), (i=0, 1, 2, . . . m-1)contained in the first candidate group 0₁. Then, the second candidategroup setting unit 432 obtains the corresponding candidate for thetransmitted signal x₁ only for one of the symbol replicas x₀^((min))(c_(1i)).

FIG. 13 is a diagram depicting one example of the first candidate groupφ₁. Here, the transmitted signals x₀ and x₁ are both modulated by QPSK.As depicted in FIG. 13, x₀ ^((min))(c_(1i)) (m=0 to 3) is a symbolreplica corresponding to one of the symbols “01”, “10”, and “11”.Therefore, the symbol replica that gives symbol “00” for the transmittedsignal x₀ is not a candidate for the transmitted signal x₀. Accordingly,the second candidate group setting unit 432 obtains the correspondingcandidate for the transmitted signal x₁ only for the symbol replicacorresponding to one of the symbols “01”, “10”, and “11” of thetransmitted signal x₀. In this way, the receiving apparatus according tothe third embodiment can reduce the amount of computation in thetransmitted signal demultiplexing process by reducing the number oftimes that the second candidate group setting unit 432 has to performthe quadrant detection.

Alternatively, after the second candidate group setting unit 432 hasconstructed the second candidate group, the first candidate groupsetting unit 431 may obtain the corresponding candidate for thetransmitted signal x₀ only for the candidate for the transmitted signalx₁ contained in the second candidate group.

Next, a receiving apparatus according to a fourth embodiment will bedescribed. The receiving apparatus according to the fourth embodimenthas three or more antennas and receiving units coupled to the respectiveantennas, and demultiplexes the transmitted signals from the signalsreceived by the respective antennas. As an example, the followingdescription is given by assuming that the receiving apparatus has threeantennas and three receiving units coupled to the respective antennas.

FIG. 14 is a diagram schematically illustrating the configuration of thestream demultiplexer 353 in the receiving apparatus according to thefourth embodiment. The stream demultiplexer 353 includes a channelinterchanging unit 41, a QR-decomposition unit 42′, a candidate groupsetting unit 43′, a common group searching unit 44, a metric calculatingunit 45, a minimum value searching unit 46, an additional metriccalculating unit 47, and a logarithmic likelihood ratio computing unit48.

These units constituting the stream demultiplexer 353 may be implementedas separate computing circuits. Alternatively, these units constitutingthe stream demultiplexer 353 may be integrated into a single computingcircuit implementing the functions of the respective units.

In FIG. 14, the units constituting the stream demultiplexer 353 aredesignated by the same reference numerals as those used to designate thecorresponding component elements of the stream demultiplexer 35according to the first embodiment depicted in FIG. 2.

The QR-decomposition unit 42′ QR-decomposes the channel matrix estimatedby the channel estimator 34 or the transformed channel matrix generatedby the channel interchanging unit 41.

The relationship between the transmitted signals and the receivedsignals is expressed by the following equation using the channel matrix.

$\begin{matrix}{{Y = {{HX} + n}}{\begin{pmatrix}y_{0} \\y_{1} \\y_{2}\end{pmatrix} = {{\begin{pmatrix}h_{00} & h_{01} & h_{02} \\h_{10} & h_{11} & h_{12} \\h_{20} & h_{21} & h_{22}\end{pmatrix}\begin{pmatrix}x_{0\;} \\x_{1} \\x_{2\;}\end{pmatrix}} + \begin{pmatrix}n_{0} \\n_{1} \\n_{2}\end{pmatrix}}}} & (18)\end{matrix}$

where x₀ to x₂ represent the signals transmitted out from the threeantennas of the transmitting apparatus. The transmitted signal vector Xis a vector whose elements are the transmitted signals x₀ to x₂. On theother hand, y₀ to y₂ represent the signals received via the respectiveantennas of the receiving apparatus. The received signal vector Y is avector whose elements are the received signals y₀ to y₂. The matrix Hindicates the channel matrix whose elements h_(ij) are each obtained,for example, as a channel impulse response to a pilot signal. The vectorn indicates the noise vector whose elements n₀ to n₂ represent the noisecomponents contained in the received signals y₀ to y₂, respectively.

The QR-decomposition unit 42′ QR-decomposes the channel matrix Hreceived from the channel estimator 34 into a unitary matrix Q and anupper triangular matrix R as shown in the following equation.

$\begin{matrix}{H = {{{QR}\begin{pmatrix}h_{00} & h_{01} & h_{02} \\h_{10} & h_{11} & h_{12} \\h_{20} & h_{21} & h_{22}\end{pmatrix}} = {\begin{pmatrix}q_{00} & q_{01} & q_{02} \\q_{10} & q_{11} & q_{12} \\q_{20} & q_{21} & q_{22}\end{pmatrix}\begin{pmatrix}r_{00} & r_{01} & r_{02} \\0 & r_{11} & r_{12} \\0 & 0 & r_{22}\end{pmatrix}}}} & (19)\end{matrix}$

Then, the QR-decomposition unit 42′ multiplies both sides of equation(18) from the left by the Hermitian conjugate Q^(H) of the unitarymatrix Q. In this way, the QR-decomposition unit 42′ obtains the unitarytransformed vector z by unitary-transforming the received signal vectorY. The relationship between the unitary transformed vector z, the uppertriangular matrix R, and the transmitted signal vector X is expressed bythe following equation.

$\begin{matrix}{z = {{Q^{H}Y} = {{{Q^{H}{QRX}} + {Q^{H}n}} = {{{RX} + {Q^{H}{n\begin{pmatrix}z_{0} \\z_{1} \\z_{2}\end{pmatrix}}}} = {{\begin{pmatrix}r_{00} & r_{01} & r_{02} \\0 & r_{11} & r_{12} \\0 & 0 & r_{22}\end{pmatrix}\begin{pmatrix}x_{0} \\x_{1} \\{x_{2}\;}\end{pmatrix}} + {\begin{pmatrix}q_{00}^{*} & q_{10}^{*} & q_{20}^{*} \\q_{01}^{*} & q_{11}^{*} & q_{21}^{*} \\q_{02}^{*} & q_{12}^{*} & q_{22}^{*}\end{pmatrix}\begin{pmatrix}n_{0} \\n_{1} \\n_{2}\end{pmatrix}}}}}}} & (20)\end{matrix}$

where unitary transformed signals z₀ to z₂ are the elements of theunitary transformed vector z.

Further, the QR-decomposition unit 42′ QR-decomposes the transformedchannel matrix H^((abc)) generated by the channel interchanging unit 41into a unitary matrix Q^((abc)) and an upper triangular matrix R^((abc))in like manner. Then, the QR-decomposition unit 42′ multiplies theequation expressing relationship between the received signal vector, thetransformed channel matrix, and the transmitted signal vector by theHermitian conjugate Q^((abc)H) of the unitary matrix Q^((abc)). In thisway, the unitary transformed vector z^((abc)) is obtained byunitary-transforming the received signal vector Y. The relationshipbetween the unitary transformed vector z^((abc)), the upper triangularmatrix R^((abc)), and the transmitted signal vector X^((abc)) isexpressed by the following equation.

$\begin{matrix}{z^{({abc})} = {{Q^{{({abc})}H}Y} = {{{Q^{{({abc})}H}Q^{({abc})}R^{({abc})}X^{({abc})}} + {Q^{{({abc})}H}n}} = {{{R^{({abc})}X^{({abc})}} + {Q^{{({abc})}H}{n\begin{pmatrix}z_{0}^{({abc})} \\z_{1}^{({abc})} \\z_{2}^{({abc})}\end{pmatrix}}}} = {{\begin{pmatrix}r_{00}^{({abc})} & r_{01}^{({abc})} & r_{02}^{({abc})} \\0 & r_{11}^{({abc})} & r_{12}^{({abc})} \\0 & 0 & r_{22}^{({abc})}\end{pmatrix}\begin{pmatrix}x_{a} \\x_{b} \\x_{c}\end{pmatrix}} + {\begin{pmatrix}q_{00}^{{({abc})}*} & q_{10}^{{({abc})}*} & q_{20}^{{({abc})}*} \\q_{01}^{{({abc})}*} & q_{11}^{{({abc})}*} & q_{21}^{{({abc})}*} \\q_{02}^{{({abc})}*} & q_{12}^{{({abc})}*} & q_{22}^{{({abc})}*}\end{pmatrix}\begin{pmatrix}n_{a} \\n_{b} \\n_{c\;}\end{pmatrix}}}}}}} & (21)\end{matrix}$

In equation (21), a, b, and c are each 0, 1, or 2, and a≠b≠c. TheQR-decomposition unit 42′ passes the unitary transformed vectors z andz^((abc)), the upper triangular matrices R and R^((abc)), etc., to thecandidate setting group 43′.

The candidate group setting unit 43′ obtains a set of candidates for thelikely transmitted signals. Referring to equation (20), it is seen thatthe unitary transformed vector signal z₀ is related to all of thetransmitted signals. Therefore, based on equation (20), the candidategroup setting unit 43′ obtains an estimate of the transmitted signal x₀by canceling the components of the transmitted signals x₁ and x₂ fromthe unitary transformed signal z₀.

When the transmitted signals x₁ and x₂ are c_(1i) and c_(2i) (i=0, 1, .. . , m₁-1, j=0, 1, . . . , m₂-1), respectively, the estimate u_(0ij) ofthe transmitted signal x₀ is expressed by the following equation. Here,m₁ and m₂ each represent the number of values that can be taken in themodulation scheme applied to the transmitted signal x₁ or x₂,respectively.

$\begin{matrix}{u_{0{ij}} = \frac{z_{0} - {r_{01}c_{1i}} - {r_{02}c_{2j}}}{r_{00}}} & (22)\end{matrix}$

The candidate group setting unit 43′, for example, similarly to thefirst candidate group setting unit 431, performs the quadrant detectionon the estimate u_(0ij) and determines the symbol replicax^((min))(c_(1i), c_(2j)) of the transmitted signal x₀ which is closestto the estimate u_(0ij). Then, the candidate group setting unit 43′ sets{x^((min))(c_(1i), c_(2j)), c_(1i), c_(2j)} as the transmitted signalcandidate set.

The candidate group setting unit 43′ obtains the estimate u_(0ij) of thetransmitted signal x₀ for each set of the symbol replicas c_(1i) andc_(2i) by substituting the symbol replicas c_(1i) and c_(2j) intoequation (22). Then, by performing the above process on each of the thusobtained estimates u_(0ij), the candidate group setting unit 43′ obtainsthe first candidate group which is a collection of transmitted signalcandidate sets.

Similarly, from the equation (21) obtained based on the transformedchannel matrix H^((abc)), the candidate group setting unit 43′ obtainsthe n-th candidate group which is a collection of transmitted signalcandidate sets. Here, n is an integer not smaller than 2 but not largerthan 6 which is the maximum number that the sum of a, b, and c can take.In this case, if the transmitted signals x_(b) and x_(c) are symbolreplicas c_(bi) and c_(cj) (i=0, 1, . . . , m_(b)-1, j=0, 1, . . . ,m_(c)-1), respectively, the estimate u_(aij) of the transmitted signalx_(a) is expressed by the following equation. Here, m_(b) and m_(c) eachrepresent the number of values that can be taken in the modulationscheme applied to the transmitted signal x_(b) or x_(c), respectively.

$\begin{matrix}{u_{aij} = \frac{z_{0}^{({abc})} - {r_{01}^{({abc})}c_{bi}} - {r_{02}^{({abc})}c_{cj}}}{r_{00}^{({abc})}}} & (23)\end{matrix}$

The candidate group setting unit 43′ performs the quadrant detection onthe estimate u_(aij) and determines the symbol replica x_(a) ^((min))(c_(bi), c_(ci)) of the transmitted signal x_(a) which is closest to theestimate u_(aij). Then, the candidate group setting unit 43′ sets {x_(a)^((min)) (c_(bi), c_(cj)), c_(bi), c_(cj)} as the transmitted signalcandidate set. Each time the candidate group is obtained, the candidategroup setting unit 43′ passes the candidate group to the common groupsearching unit 44.

The channel interchanging unit 41 creates at least one transformedchannel matrix H^((abc)) by interchanging the order of the columns inthe channel matrix H. Such transformed channel matrices H^((abc)) arecreated so that the order of the columns is different from one matrix toanother. In the present embodiment, since the number of transmittedsignals is 3, the number of transformed channel matrices H^((abc)) is 5(=₃P₃-1) at maximum. If the number of transformed channel matricesH^((abc)) to be created is smaller than the number of transmittedsignals, it is preferable that the channel interchanging unit 41 createseach transformed channel matrix H^((abc)) so that the transmitted signalx_(a) located in the uppermost row in the above equation (21) isdifferent from the transmitted signal x₀ as well as from x_(a) in theother transformed channel matrix. In this way, the transmitted signalwhose estimate is obtained by the equation (22) or (23) can be madedifferent for each channel matrix or each transformed channel matrix,respectively. As a result, since the candidate groups created accordingto the channel matrix and the transformed channel matrix are alsodifferent, the stream demultiplexer 353 can globally search for thetransmitted signal candidate sets.

Each time the transformed channel matrix H^((abc)) is created, thechannel interchanging unit 41 passes the created transformed channelmatrix H^((abc)) to the QR-decomposition unit 42′. Further, the channelinterchanging unit 41 stores the order of the columns in the createdtransformed channel matrix H^((abc)) into a buffer memory incorporatedin the channel interchanging unit 41. Then, by referring to the order ofthe columns stored in the buffer memory, the channel interchanging unit41 selects the order of the columns not yet stored, and interchanges theorder of the columns in the channel matrix so as to match the selectedorder of the columns. The channel interchanging unit 41 can thus createa new transformed channel matrix which is different from any previouslycreated transformed channel matrix H^((abc)).

Each time the candidate group is received from the candidate groupsetting unit 43′, the common group searching unit 44 stores thecandidate group into a buffer memory incorporated in the common groupsearching unit 44. Then, when the next candidate group is received, thecommon group searching unit 44 searches for transmitted signal candidatesets common to the two candidate groups. The common group searching unit44 then groups together the transmitted signal candidate sets common tothe two candidate groups and stores them as a common group into thebuffer memory incorporated in the common group searching unit 44.

Thereafter, each time the subsequent candidate group is received, thecommon group searching unit 44 searches for transmitted signal candidatesets that are common between the received candidate group and the commongroup, and stores a group of such common transmitted signal candidatesets as a new common group into the buffer memory. After the transmittedsignal candidate sets common to all the candidate groups have beenextracted, the common group searching unit 44 passes the thus extractedtransmitted signal candidate sets to the metric calculating unit 45. Themetric calculating unit 45 calculates the metrics for the extractedtransmitted signal candidate sets. The minimum value searching unit 46obtains the minimum value among the thus calculated metrics, andestimates that the transmitted signal candidate set corresponding to theminimum value represents the actually transmitted signal set.

The operation flowchart of the transmitted signal demultiplexing processperformed under control of the stream demultiplexer 353 is the same asthe operation flowchart illustrated in FIGS. 7A, 7B, and 8, with theonly difference that the process from step S105 to step S110 is repeatedthe same number of times as the number of transformed channel matricesto be created.

The stream demultiplexer 353 may repeat the process from step S105 tostep S110 a predetermined number of times. Alternatively, the streamdemultiplexer 353 may stop repeating the process from step S105 to stepS110 when the number of transmitted signal candidate sets contained inthe common group has dropped to or below a predetermined number.

In the receiving apparatus according to the fourth embodiment also,since the metric is calculated only for the transmitted signal candidatesets extracted by the common group searching unit, the amount ofcomputation needed to demultiplex the transmitted signals from thesignals received by three or more antennas can be reduced.

It will be appreciated that the present invention is not limited to theabove specific embodiments. For example, the stream demultiplexeraccording to any one of the first, third, and fourth embodiments neednot necessarily include the QR-decomposition unit. In that case, thecandidate group setting unit obtains the first and second candidategroups by using the equation expressing relationship between the channelmatrix or transformed channel matrix, the received signal vector, andthe transmitted signal vector. For example, using equation (4), theestimate u_(0i) of the transmitted signal x₀ is obtained as a residualcomponent as shown in the following equation by canceling the componentrelating to the symbol replica c_(1i) of the transmitted signal x₁ fromthe received signal y₀.

$\begin{matrix}{u_{0j} = \frac{y_{0} - {h_{01}c_{1i}}}{h_{00}}} & (24)\end{matrix}$

Then, as in the above embodiments, the candidate group setting unit canobtain the symbol replica x₀(c_(1i)) of the transmitted signal x₀ thatis closest to the estimate u_(0i), and can thus set (x₀(c_(1i)), c_(1i))as the transmitted signal candidate set to be included in the firstcandidate group. Likewise, using equation (5), the estimate u_(1i) ofthe transmitted signal x₁ is obtained as a residual component as shownin the following equation by canceling the component relating to thesignal replica c_(0i) of the transmitted signal x₀ from the receivedsignal y₁.

$\begin{matrix}{u_{1j} = \frac{y_{1} - {h_{10}c_{0i}}}{h_{11}}} & (25)\end{matrix}$

Then, as in the above embodiments, the candidate group setting unit canobtain the symbol replica x₁(c_(0i)) of the transmitted signal x_(i)that is closest to the estimate u_(1i), and can thus set (c_(0i),x₁(c_(0i))) as the transmitted signal candidate set to be included inthe second candidate group.

Alternatively, using equation (4), the candidate group setting unit mayobtain the estimate u_(1i) of the transmitted signal x₁ by canceling thecomponent relating to the signal replica c_(0i) of the transmittedsignal x₀ from the received signal y₁. In this way, when the candidategroup setting unit obtains the estimate of the transmitted signaldifferent for each received signal by noting the different receivedsignals, the channel interchanging unit may also be omitted.

Further, by substituting the transmitted signal set, for example, intothe first term on the right-hand side of equation (4), the metriccalculating unit and the additional metric calculating unit can eachcalculate the estimated transmitted signal set.

The receiving apparatus according to the fourth embodiment may becombined with the receiving apparatus according to the secondembodiment. In this case, the stream demultiplexer 353 includes theranking unit for determining the ranks of the transmitted signalcandidate sets. Then, from the unitary transformed signal z₂ or z_(c)that depends only on one transmitted signal, for example, in equation(20) or (21), the ranking unit obtains the estimate of the correspondingtransmitted signal x₂ or x_(c). Then, by performing the quadrantdetection on the estimate, the ranking unit assigns the ranking valuesin order of closeness to the estimate to the symbol replicascorresponding to the values that the transmitted signal x₂ or x_(c) cantake. The common group searching unit then allocates priorities to thetransmitted signal candidate sets contained in the common group inaccordance with the ranking values assigned to the respective candidatesets, and selects a predetermined number of candidate sets in decreasingorder of priority.

Alternatively, the receiving apparatus according to the fourthembodiment may be combined with the receiving apparatus according to thethird embodiment. Further, the receiving apparatus according to any oneof the first to third embodiments may include only one QR-decompositionunit and only one candidate group setting unit, as in the receivingapparatus according to the fourth embodiment. Then, this oneQR-decomposition unit may QR-decompose not only the channel matrix butalso the transformed channel matrix, and this one candidate groupsetting unit may create candidate groups according to the channel matrixand the transformed channel matrix, respectively.

Further, a computer program having instructions for causing a processorto implement the functions of the respective units constituting thestream demultiplexer in the receiving apparatus according to any one ofthe above embodiments may be delivered to the receiving apparatus via aradio link. Then, the receiving apparatus may cause the streamdemultiplexer to perform the transmitted signal demultiplexing processby loading the computer program into the processor contained in thereceiving apparatus.

A communication apparatus capable of both signal transmission and signalreception using MIMO technology is constructed by combining thecomponent elements of the transmitting apparatus 2 with the componentelements of the receiving apparatus 3. In this case, the antennas 21-1and 21-2 of the transmitting apparatus 2 and the antennas 31-1 and 31-2of the receiving apparatus 3 are replaced by a set of common antennas.Each common antenna is coupled by the action of a duplexer to one of thetransmitting units 25-1 and 25-2 in the transmitting apparatus 2 or toone of the receiving units 32-1 and 32-2 in the receiving apparatus 3,whichever is selected.

Next, a description will be given of a mobile station and a base stationapparatus in a mobile communication system that employs the receivingapparatus or communication apparatus according to any one of the aboveembodiments.

FIG. 15 is a diagram schematically illustrating the configuration of thebase station apparatus incorporating the above-described transmittingapparatus and receiving apparatus. The base station apparatus 100includes a line terminating unit 101, a baseband processing unit 102, acall control unit 103, a plurality of communication units 104-1 to104-n, and a plurality of antennas 105-1 to 105-n. Here, n is a naturalnumber not smaller than 2. The baseband processing unit 102, the callcontrol unit 103, and the communication units 104-1 to 104-n may beprovided as separate circuits or may be implemented together on a singleintegrated circuit.

The line terminating unit 101 has a communication interface forconnecting to a core network. The line terminating unit 101 terminatesthe core network to which a host apparatus is connected. The lineterminating unit 101 receives from the core network a downlink signal tobe transmitted to a mobile station, and passes the downlink signal tothe baseband processing unit 102. On the other hand, the basebandprocessing unit 102 passes an uplink signal received from the mobilestation to the line terminating unit 101, which then outputs the uplinksignal onto the core network.

The baseband processing unit 102 implements the functions of thecodeword generating unit 22, encoding unit 23, modulation unit 24, andcontrol unit 26 provided in the transmitting apparatus 2 according toeach of the above embodiments. The baseband processing unit 102 furtherimplements the functions of the demodulation unit 33, decoding unit 36,and data combining unit 37 provided in the receiving apparatus 3according to each of the above embodiments.

The baseband processing unit 102 determines the precoding matrix and thenumber of streams, MOD, and TBS for each codeword, based on the feedbackinformation received from the mobile station apparatus. Further, thebaseband processing unit 102 splits the downlink signal received fromthe core network into codewords each having a length defined by thetransport block size TBS. The baseband processing unit 102 applies errorcorrection coding to each codeword. The baseband processing unit 102generates data streams by splitting the encoded codeword in accordancewith the above determined number of streams. Then, the basebandprocessing unit 102 generates transmit signals by quadrature-modulatingthe data streams in accordance with the modulation mode MOD. Thebaseband processing unit 102 outputs each transmit signal to acorresponding one of the antennas 105-1 to 105-n by referring to theprecoding matrix.

On the other hand, the uplink signal received via the antennas 105-1 to105-n is passed via the respective communication units 104-1 to 104-n tothe baseband processing unit 102, which then demultiplexes from theuplink signal the signals transmitted out from the respective antennasof the mobile station apparatus. The baseband processing unit 102 thenreconstructs each encoded codeword by combining the transmitted signalsthus demultiplexed. The baseband processing unit 102 applies errorcorrection decoding to each encoded codeword. The baseband processingunit 102 combines the thus decoded codewords to recover the originaluplink signal. Then, the baseband processing unit 102 outputs the uplinksignal onto the core network via the line terminating unit 101.

Further, the baseband processing unit 102 calculates the feedbackinformation, such as CQI value, rank value, and precoding vector, to befed back to the mobile station apparatus, and transmits the feedbackinformation to the mobile station apparatus via one of the communicationunits 104-1 to 104-n.

The call control unit 103 performs call control processing such aspaging, call answering, call termination, handover, etc., between thebase station apparatus 100 and the mobile station apparatus such as aportable terminal communicating via the base station apparatus 100.Then, the call control unit 103 instructs the baseband processing unit102 to start or terminate the operation, in accordance with the resultof the call control processing.

The communication units 104-1 to 104-n each include one of thetransmitting units provided in the transmitting apparatus 2 according toeach of the above embodiments and one of the receiving units provided inthe receiving apparatus 3. The transmitting unit and receiving unitprovided in each of the communication units 104-1 to 104-n are coupledvia a duplexer (not illustrated) to one of the antennas 105-1 to 105-n.The communication units 104-1 to 104-n amplify the downlink signalreceived from the baseband processing unit 102, and transmit out theamplified downlink signal via the antennas 105-1 to 105-n.

Further, the communication units 104-1 to 104-n receive via the antennas105-1 to 105-n the uplink signal transmitted from the mobile stationapparatus. Then, the communication units 104-1 to 104-n amplify thereceived unlink signal and pass it to the baseband processing unit 102.

Each communication unit in the base station apparatus may be provided asan apparatus independent of the base station apparatus proper. In thatcase, each communication unit is coupled to the base station apparatusproper, for example, by an optical fiber. Then, each communication unitand the base station apparatus proper communicate with each other inaccordance with a communication standard such as Common Public RadioInterface (CPRI).

FIG. 16 is a diagram schematically illustrating the configuration of themobile station apparatus incorporating the above-described transmittingapparatus and receiving apparatus. The mobile station apparatus 200includes a control unit 201, a baseband processing unit 202, a callcontrol unit 203, a plurality of communication units 204-1 to 204-n, anda plurality of antennas 205-1 to 205 n. Here, n is a natural number notsmaller than 2. The control unit 201, the baseband processing unit 202,the call control unit 203, and the communication units 204-1 to 204-nmay be provided as separate circuits or may be implemented together on asingle integrated circuit.

The control unit 201 controls the entire operation of the mobile stationapparatus 200. The control unit 201 executes various applicationprograms that run on the mobile station apparatus 200. For this purpose,the control unit 201 includes a processor, a nonvolatile memory, and avolatile memory. When an application for performing communications suchas voice or data communications is started up by a user operation via anoperation unit (not illustrated) such as a keypad incorporated in themobile station apparatus 200, the control unit 201 operates the callcontrol unit 203 in accordance with the application. Then, the controlunit 201 applies information source coding to the voice signal acquiredvia a microphone (not illustrated) incorporated in the mobile stationapparatus 200 or to the data requested for transmission by theapplication. The control unit 201 passes the thus processed signal as anuplink signal to the baseband processing unit 202. On the other hand,when a downlink signal is received from the baseband processing unit202, the control unit 201 applies information source decoding to it andrecovers the data or voice signal. The control unit 201 passes the voicesignal to a speaker (not illustrated) incorporated in the mobile stationapparatus 200. Or, the control unit 201 displays the acquired data on adisplay (not illustrated) incorporated in the mobile station apparatus200.

The baseband processing unit 202 implements the functions of thecodeword generating unit 22, encoding unit 23, modulation unit 24, andcontrol unit 26 provided in the transmitting apparatus 2 according toeach of the above embodiments. The baseband processing unit 202 furtherimplements the functions of the demodulation unit 33, decoding unit 36,and data combining unit 37 provided in the receiving apparatus 3according to each of the above embodiments.

The baseband processing unit 202 determines the precoding matrix and thenumber of streams, MOD, and TBS for each codeword, based on the feedbackinformation received from the base station apparatus. Further, thebaseband processing unit 202 splits the uplink signal into codewordseach having a length defined by the transport block size TBS. Thebaseband processing unit 202 applies error correction coding to eachcodeword. The baseband processing unit 202 generates data streams bysplitting the encoded codeword in accordance with the above determinednumber of streams. Then, the baseband processing unit 202 generatestransmit signals by quadrature-modulating the data streams in accordancewith the modulation mode MOD. The baseband processing unit 202 supplieseach transmit signal to a corresponding one of the communication units204-1 to 204-n by referring to the precoding matrix.

On the other hand, the downlink signal, when received, is passed via therespective communication units 204-1 to 204-n to the baseband processingunit 202, which then demultiplexes from the downlink signal the signalstransmitted out from the respective antennas of the base stationapparatus. The baseband processing unit 202 then reconstructs eachencoded codeword by combining the transmitted signals thusdemultiplexed. The baseband processing unit 202 applies error correctiondecoding to each encoded codeword. The baseband processing unit 202combines the thus decoded codewords to recover the original downlinksignal. Then, the baseband processing unit 202 passes the downlinksignal to the control unit 201.

Further, the baseband processing unit 202 calculates the feedbackinformation, such as CQI value, rank value, and precoding vector, to befed back to the base station apparatus, and transmits the feedbackinformation to the base station apparatus via one of the antennas 205-1to 205-n.

The call control unit 203 performs call control processing such aspaging, call answering, call termination, handover, etc., between themobile station apparatus 200 and the base station apparatus. Then, thecall control unit 203 instructs the baseband processing unit 202 tostart or terminate the operation, in accordance with the result of thecall control processing.

The communication units 204-1 to 204-n each include one of thetransmitting units provided in the transmitting apparatus 2 according toeach of the above embodiments and one of the receiving units provided inthe receiving apparatus 3. The transmitting unit and receiving unitprovided in each of the communication units 204-1 to 204-n are coupledvia a duplexer (not illustrated) to one of the antennas 205-1 to 205-n.The communication units 204-1 to 204-n amplify the uplink signalreceived from the baseband processing unit 202, and transmit out theamplified uplink signal via the antennas 205-1 to 205-n.

Further, the communication units 204-1 to 204-n receive via the antennas205-1 to 205-n the downlink signal transmitted from the base stationapparatus. Then, the communication units 204-1 to 204-n amplify thereceived downlink signal and pass it to the baseband processing unit202.

The mobile station apparatus 200 may further include an interface unitfor connecting the mobile station apparatus 200 to another apparatus viaa data transmission link such as a Peripheral Component Interconnect(PCI) bus or a Universal Serial Bus (USB). In that case, the interfaceunit is coupled to the control unit 201, and outputs signals receivedfrom the control unit 201 onto the data transmission link fortransmission to that other apparatus. On the other hand, when a signalis received from that other apparatus via the data transmission link,the interface unit passes the signal to the control unit 201.

All of the examples and conditional language recited herein are intendedfor pedagogical purposes to aid the reader in understanding theinvention and the concepts contributed by the inventor to furthering theart, and are to be construed as being without limitation to suchspecifically recited examples and conditions, nor does the organizationof such examples in the specification relate to a showing of superiorityand inferiority of the invention. Although the embodiments of thepresent invention have been described in detail, it should be understoodthat the various changes, substitutions, and alterations could be madehereto without departing from the spirit and scope of the invention.

1. A communication apparatus comprising: a plurality of antennas; aplurality of receiving units which are each coupled to one of saidplurality of antennas, and which respectively acquire received signalsby receiving, via said coupled antennas, a plurality of signalstransmitted from a transmitting apparatus having a plurality ofantennas; a candidate group setting unit which, based on a first channelmatrix describing a communication channel between said plurality oftransmitted signals and said plurality of received signals, calculates afirst residual component by canceling a component corresponding to acandidate or candidates for a first other transmitted signal or signalsother than a first transmitted signal among said plurality oftransmitted signals from a first signal corresponding to at least one ofsaid plurality of received signals and having components correspondingto all of said plurality of transmitted signals, determines a candidatefor said first transmitted signal by selecting a value closest to saidfirst residual component from among values that said first transmittedsignal can take, and constructs a first candidate group as a collectionof candidate sets each comprising a candidate for said first transmittedsignal and a candidate or candidates for said first other transmittedsignal or signals, and which, based on a second channel matrixdescribing a communication channel between said plurality of transmittedsignals and said plurality of received signals, calculates a secondresidual component by canceling a component corresponding to a candidateor candidates for a second other transmitted signal or signals otherthan a second transmitted signal among said plurality of transmittedsignals from a second signal corresponding to at least one of saidplurality of received signals and having components corresponding to allof said plurality of transmitted signals, determines a candidate forsaid second transmitted signal by selecting a value closest to saidsecond residual component from among values that said second transmittedsignal can take, and constructs a second candidate group as a collectionof candidate sets each comprising a candidate for said secondtransmitted signal and a candidate or candidates for said second othertransmitted signal or signals; a common group searching unit whichconstructs a common group by selecting any transmitted signal candidateset that is common between said first candidate group and said secondcandidate group; a metric calculating unit which, for each transmittedsignal candidate set contained in said common group, computes anestimated received signal set corresponding to said each transmittedsignal candidate set, and calculates a distance between said estimatedreceived signal set and said plurality of received signals; and a signalestimating unit which estimates that the transmitted signal candidateset that minimizes said distance represents the set of said plurality oftransmitted signals.
 2. The communication apparatus according to claim1, further comprising a channel interchanging unit which creates saidsecond channel matrix by interchanging the order of columns in saidfirst channel matrix.
 3. The communication apparatus according to claim1, wherein said first channel matrix and said second channel matrix arethe same channel matrix.
 4. The communication apparatus according toclaim 1, further comprising a ranking unit which, for each of saidtransmitted signal candidate sets contained in said first candidategroup, calculates a first ranking value that provides a measure of thelikelihood that said each transmitted signal candidate set representssaid plurality of transmitted signals, and which, for each of saidtransmitted signal candidate sets contained in said second candidategroup, calculates a second ranking value that provides a measure of thelikelihood that said each transmitted signal candidate set representssaid plurality of transmitted signals, and wherein based on said firstranking value and said second ranking value, said common group searchingunit allocates priority to each of said transmitted signal candidatesets contained in said common group, said priority increasing inincreasing order of the likelihood of said each transmitted signalcandidate set representing said plurality of transmitted signals, andsaid metric calculating unit calculates said distance for apredetermined number of candidate sets selected in decreasing order ofsaid priority.
 5. The communication apparatus according to claim 4,further comprising a decomposition unit which decomposes said firstchannel matrix into a unitary matrix and a triangular matrix and obtainsa plurality of unitary transformed signals by multiplying a receivedsignal vector, whose elements are said plurality of received signals, bya Hermitian conjugate of said unitary matrix, and wherein said candidategroup setting unit calculates an estimate of a third transmitted signalbased on said triangular matrix and on a unitary transformed signalselected as having a component only of said third transmitted signalfrom among said plurality of unitary transformed signals, said thirdtransmitted signal being one of said plurality of transmitted signalsbut different from said first transmitted signal, and said first rankingvalue assigned to each of said transmitted signal candidate setscontained in said first candidate group is set so as to indicate thatsaid likelihood is greater as a candidate for said third transmittedsignal contained in said each transmitted signal candidate set is closerto said estimate.
 6. The communication apparatus according to claim 5,wherein said candidate group setting unit constructs said firstcandidate group by using only a predetermined number of candidates forsaid third transmitted signal that are selected from among thecandidates for said third transmitted signal in order of closeness tothe estimate of said third transmitted signal.
 7. The communicationapparatus according to claim 1, wherein said candidate group settingunit constructs said second candidate group by including as thecandidate or candidates for said second other transmitted signal orsignals only the values selected, from among the values that said firsttransmitted signal can take, as the candidates for said firsttransmitted signal contained in said first candidate group.
 8. Thecommunication apparatus according to claim 1, wherein said candidategroup setting unit detects a quadrant to which said first residualcomponent belongs, based on the sign of a real component of said firstresidual component and the sign of an imaginary component thereof, anddetermines the value closest to said first residual component by judgingthat, of the values that said first transmitted signal can take, anyvalue belonging to said quadrant is closer to said first residualcomponent than a value not belonging to said quadrant.
 9. Thecommunication apparatus according to claim 1, further comprising: anadditional metric calculating unit which calculates said distance as asecond distance for a set of candidates for transmitted signalsincluding transmitted signals each having one inverted bit with respectto one of said transmitted signals contained in said estimatedtransmitted signal set; and a logarithmic likelihood ratio computingunit which computes a logarithmic likelihood ratio by calculating adifference between said first distance and said second distance.
 10. Thecommunication apparatus according to claim 1 as a base stationapparatus, further comprising: a decoding unit which recovers an uplinksignal by decoding said plurality of transmitted signals; and a lineterminating unit which outputs said uplink signal onto a core network.11. The communication apparatus according to claim 1 as a mobile stationapparatus, further comprising a decoding unit which recovers a downlinksignal by decoding said plurality of transmitted signals.
 12. Acommunication method performed by a communication apparatus, comprising:based on a first channel matrix describing a communication channelbetween a plurality of signals transmitted from a transmitting apparatushaving a plurality of antennas and a plurality of received signalsobtained by receiving said plurality of transmitted signals by aplurality of antennas incorporated in a receiving apparatus, calculatinga first residual component by canceling a component corresponding to acandidate or candidates for a first other transmitted signal or signalsother than a first transmitted signal among said plurality oftransmitted signals from a first signal corresponding to at least one ofsaid plurality of received signals and having components correspondingto all of said plurality of transmitted signals; determining a candidatefor said first transmitted signal by selecting a value closest to saidfirst residual component from among values that said first transmittedsignal can take; and constructing a first candidate group as acollection of candidate sets each comprising a candidate for said firsttransmitted signal and a candidate or candidates for said first othertransmitted signal or signals; based on a second channel matrixdescribing a communication channel between said plurality of transmittedsignals and said plurality of received signals, calculating a secondresidual component by canceling a component corresponding to a candidateor candidates for a second other transmitted signal or signals otherthan a second transmitted signal among said plurality of transmittedsignals from a second signal corresponding to at least one of saidplurality of received signals and having components corresponding to allof said plurality of transmitted signals; determining a candidate forsaid second transmitted signal by selecting a value closest to saidsecond residual component from among values that said second transmittedsignal can take; and constructing a second candidate group as acollection of candidate sets each comprising a candidate for said secondtransmitted signal and a candidate or candidates for said second othertransmitted signal or signals; constructing a common group by selectingany transmitted signal candidate set that is common between said firstcandidate group and said second candidate group; for each transmittedsignal candidate set contained in said common group, computing anestimated received signal set corresponding to said each transmittedsignal candidate set, and calculating a distance between said estimatedreceived signal set and said plurality of received signals; andestimating that the transmitted signal candidate set that minimizes saiddistance represents the set of said plurality of transmitted signals.